Exciting New Partnership: Optimum and Qlik Join Forces to Transform Data Analytics for Clients
With Seamless Data Integration and Cutting-Edge Visualization, This Partnership Will Drive Business Growth and Empower Data-Driven Decisions for Businesses of All Sizes
HOUSTON, TX / ACCESSWIRE / August 8, 2024 / Optimum Consultancy Services, a leader in IT consulting that specializes in data, business intelligence (BI), and artificial intelligence (AI) solutions, is thrilled to announce a new strategic partnership with Qlik®, a renowned leader in data integration and data analytics solutions.
This partnership is set to transform the way businesses leverage data for strategic decision-making. Through this collaboration, Optimum will integrate Qlik’s cutting-edge BI tools and data integration solutions into its service offerings. This includes the powerful Qlik Sense® platform, known for its associative analytics engine and sophisticated AI, and Qlik’s comprehensive data integration and quality solution, Qlik Talend® Cloud.
Qlik Sense Business Analyst Certification – Credly
Qlik Sense® will enable Optimum’s clients to unlock powerful insights from their data, enhancing decision-making processes with interactive dashboards, fully interactive analytics apps, and beautiful reports that are accessible on any device. Additionally, the partnership will leverage Qlik’s data integration and quality to ensure that data is not only seamlessly integrated but also maintained with the highest quality and integrity. This means clients can trust the data at their fingertips, making it easier to achieve compliance with data regulations and standards.
‘We are thrilled to partner with Qlik to enhance our clients’ data integration and analytics capabilities,’ says Nooshin Yazhari, President and CEO of Optimum. ‘This partnership not only enhances our BI and AI offerings but also strengthens our data integration and quality services, ensuring our clients have access to the best tools in the industry. We are confident that our partnership with Qlik will unlock new opportunities for our clients and drive growth for their businesses.’
Benefits for Clients:
Enhanced Data Capabilities: Clients will benefit from a seamless blend of Optimum’s expertise and Qlik’s technological prowess, leading to enhanced capabilities in data processing, analytics, and decision-making.
Managing spaces in Qlik Sense Business
Streamlined Operations: With improved data integration and quality, businesses can streamline their operations, reduce costs, and increase efficiency.
Competitive Advantage: By leveraging real-time data insights and forecasts, businesses can stay ahead of market trends and make informed strategic decisions that provide a competitive edge.
Scalability: The solutions provided are scalable, ensuring that as a business grows, its data solutions can grow with it without performance loss.
This strategic partnership is effective immediately, and Optimum is ready to assist businesses in implementing these powerful solutions to harness the full potential of their data.
Qlik Sense Business or Qlik Sense Enterprise SaaS Qalyptus
For more information about Optimum’s partnership with Qlik, please visit our Qlik offerings page or contact us at 713.505.0300 | info@optimumcs.com.
About Optimum
Optimum Consultancy Services, based in Houston, Texas, is a leading IT consulting firm focused on delivering top-tier data and business intelligence solutions. Specializing in integrating and optimizing complex data environments, Optimum leverages cutting-edge technologies, such as Qlik, to empower clients with actionable insights and tailored analytics strategies. As a trusted advisor in the IT sector, Optimum partners with industry-leading software providers to enhance its service offerings, ensuring clients receive comprehensive, state-of-the-art support that drives significant business outcomes. Known for its commitment to excellence and innovation, Optimum continually strives to transform the data capabilities of its clients nationwide.
Learn more at www.optimumcs.com.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML and data management. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. Our AI/ML solutions, both practical and scalable, lead to better decisions, faster. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
Nooshin Yazhari President and CEO nyazhari@optimumcs.com 713.505.0300
Gabby de Janasz Marketing Specialist gdejanasz@optimumcs.com 713.505.0300
Keith Parker Senior Director, Global Corporate and Executive Communications keith.parker@qlik.com 512.367.2884
SOURCE: Optimum Consultancy Services
View the original press release on newswire.com.
Financial Data Analysts: Making Sense of Big Data in FinTech
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Financial technology, or FinTech, data is the new gold. Companies are increasingly relying on vast amounts of data to make informed decisions, drive innovation, and maintain a competitive edge. This influx of data has given rise to a critical role within the industry: the Financial Data Analyst. These professionals are tasked with deciphering complex data sets to provide actionable insights that can shape the future of financial services.
Big Data has become a buzzword across various industries, but its impact on FinTech is particularly profound. With the proliferation of digital transactions, online banking, and mobile payments, the financial industry generates an enormous amount of data daily. This data includes everything from transaction records and customer behavior patterns to market trends and social media interactions. For FinTech companies, leveraging this data is not just a competitive advantage; it is a necessity.
However, the sheer volume, variety, and velocity of data generated in the financial sector can be overwhelming. This is where Financial Data Analysts come into play. Their expertise in data analysis helps FinTech companies navigate the complexities of Big Data, transforming it into valuable insights that drive business growth.
The Role of a Financial Data Analyst
Financial Data Analysts are the backbone of data-driven decision-making in FinTech. They possess a unique blend of financial acumen and data science skills, enabling them to interpret complex data sets and provide actionable recommendations. Their role extends beyond mere number-crunching; they are responsible for identifying patterns, trends, and anomalies that can inform strategic decisions.
Data Collection and Preparation
The first step in the data analysis process is data collection. Financial Data Analysts gather data from various sources, including transaction records, customer databases, market reports, and external data feeds. This data is often unstructured and requires significant cleaning and preprocessing before it can be analyzed. Data preparation involves removing duplicates, filling in missing values, and converting data into a structured format that can be easily analyzed.
Data Analysis and Interpretation
Once the data is prepared, Financial Data Analysts use a range of analytical tools and techniques to extract insights. This may involve statistical analysis, data mining, machine learning, and predictive modeling. The goal is to identify patterns, correlations, and trends that can inform business decisions. For example, a Financial Data Analyst might analyze customer transaction data to identify spending patterns, which can then be used to develop targeted marketing campaigns or personalized financial products.
Risk Management and Fraud Detection
One of the critical functions of Financial Data Analysts in FinTech is risk management. By analyzing historical data, they can identify potential risks and develop strategies to mitigate them. This is particularly important in areas such as credit risk assessment, where analysts use data to evaluate the creditworthiness of borrowers. Additionally, Financial Data Analysts play a crucial role in fraud detection. By analyzing transaction data in real-time, they can identify suspicious activities and flag potential fraud before it causes significant damage.
Compliance and Regulatory Reporting
The financial industry is heavily regulated, and FinTech companies must comply with various laws and regulations. Financial Data Analysts help ensure compliance by analyzing data to monitor adherence to regulatory requirements. They also assist in preparing regulatory reports, which are essential for maintaining transparency and avoiding legal penalties. In this way, Financial Data Analysts help FinTech companies navigate the complex regulatory landscape.
The Tools and Technologies Empowering Financial Data Analysts
The role of Financial Data Analysts is heavily reliant on technology. A wide array of tools and technologies are available to assist them in their tasks, from data visualization software to advanced machine learning algorithms. Below, we explore some of the key technologies that empower Financial Data Analysts in the FinTech industry.
Data Visualization Tools
Data visualization is a crucial aspect of data analysis. Financial Data Analysts use visualization tools to present complex data in a more understandable and actionable format. Tools like Tableau, Power BI, and Qlik allow analysts to create interactive dashboards, charts, and graphs that can be easily interpreted by non-technical stakeholders. These visualizations enable decision-makers to grasp insights quickly, facilitating more informed business decisions.
Machine Learning and AI
Machine learning and artificial intelligence (AI) are revolutionizing the way Financial Data Analysts work. These technologies enable analysts to automate complex tasks, such as predictive modeling and anomaly detection. For instance, machine learning algorithms can analyze vast amounts of data to predict future market trends or identify fraudulent activities in real-time. AI-powered tools also allow analysts to process unstructured data, such as text or social media posts, to gain additional insights.
Big Data Platforms
Handling Big Data requires specialized platforms that can store, process, and analyze large data sets efficiently. Financial Data Analysts often work with Big Data platforms like Apache Hadoop, Spark, and NoSQL databases. These platforms allow analysts to process massive data sets in parallel, reducing the time required for analysis. Additionally, cloud-based platforms like AWS, Google Cloud, and Microsoft Azure offer scalable solutions for storing and analyzing Big Data, making it more accessible for FinTech companies.
Programming Languages and Statistical Software
Financial Data Analysts rely on programming languages like Python, R, and SQL for data manipulation and analysis. Python and R are particularly popular due to their extensive libraries and frameworks for data science, such as Pandas, NumPy, and Scikit-learn. These languages allow analysts to perform complex statistical analyses, build predictive models, and automate repetitive tasks. SQL, on the other hand, is essential for querying and managing data in relational databases, making it a vital tool for data retrieval and preparation.
Challenges Faced by Financial Data Analysts
While the role of Financial Data Analysts is crucial, it is not without its challenges. The dynamic nature of the FinTech industry, coupled with the complexities of Big Data, presents several obstacles that analysts must overcome.
Data Quality and Integrity
One of the most significant challenges Financial Data Analysts face is ensuring the quality and integrity of the data they analyze. Incomplete, inconsistent, or inaccurate data can lead to erroneous conclusions, which can have severe implications for business decisions. Analysts must implement robust data cleaning and validation processes to ensure the data they work with is reliable and accurate.
Data Privacy and Security
With the increasing focus on data privacy and security, Financial Data Analysts must navigate the challenges of handling sensitive information. Ensuring compliance with data protection regulations, such as GDPR and CCPA, is paramount. Analysts must implement stringent security measures to protect data from breaches and unauthorized access. Additionally, they must anonymize data where necessary to protect individual privacy while still extracting valuable insights.
Keeping Up with Technological Advancements
The rapid pace of technological advancements in FinTech means that Financial Data Analysts must continuously update their skills and knowledge. New tools, techniques, and frameworks are constantly emerging, and staying ahead of the curve is essential for maintaining a competitive edge. This requires ongoing education and training, as well as a willingness to adapt to new technologies and methodologies.
The Future of Financial Data Analysts in FinTech
As the FinTech industry continues to evolve, the role of Financial Data Analysts is set to become even more critical. The increasing reliance on data-driven decision-making will drive demand for skilled analysts who can interpret complex data and provide actionable insights. Moreover, advancements in AI and machine learning will further enhance the capabilities of Financial Data Analysts, allowing them to tackle even more sophisticated challenges.
Expanding Roles and Responsibilities
The scope of Financial Data Analysts’ roles is likely to expand in the future. As FinTech companies continue to innovate, analysts may find themselves involved in more strategic decision-making processes. They may also take on additional responsibilities, such as developing and implementing data-driven strategies or advising on the adoption of new technologies. This expanded role will require analysts to possess not only technical skills but also strong business acumen and strategic thinking.
The Rise of Real-Time Data Analysis
The future of financial data analysis lies in real-time data analysis. As FinTech companies strive to offer more personalized and immediate services, the ability to analyze data in real-time will become increasingly important. Financial Data Analysts will need to leverage advanced technologies, such as streaming analytics platforms, to process and analyze data as it is generated. This will enable FinTech companies to make instant decisions and offer more responsive services to their customers.
The Integration of ESG Data
Environmental, Social, and Governance (ESG) factors are becoming increasingly important in the financial industry. As investors and regulators place more emphasis on sustainability, Financial Data Analysts will need to integrate ESG data into their analyses. This will involve assessing the impact of ESG factors on financial performance and identifying investment opportunities that align with sustainability goals. The ability to analyze and interpret ESG data will become a valuable skill for Financial Data Analysts in the future.
Conclusion
Financial Data Analysts play a pivotal role in making sense of Big Data. Their expertise in data collection, analysis, and interpretation enables FinTech companies to make informed decisions, manage risks, and stay ahead of the competition. As the industry continues to evolve, the demand for skilled Financial Data Analysts will only increase, making this an exciting and dynamic field to be a part of. With the right tools, skills, and knowledge, Financial Data Analysts are well-positioned to drive the future of financial technology and help companies navigate the complexities of Big Data.
PHILADELPHIA, July 30, 2024 — Qlik, a global leader in data integration, analytics, and artificial intelligence (AI), today announced the general availability of Qlik Answers, its newest self-service AI solution designed to help organizations harness the power of AI by removing the risk, embracing the complexity, and scaling the impact of AI. Qlik Answers transforms unstructured data into actionable results through generative AI, offering full explainability—a common obstacle in enterprise AI adoption.
Qlik Answers combines generative AI with Qlik’s trusted data analytics capabilities to deliver precise, contextually relevant results from extensive unstructured data sources. This solution enables customers to seamlessly integrate AI into their existing Qlik business intelligence workflows, ensuring efficient use of resources and avoiding technical debt.
“Qlik Answers is designed to help businesses use their unstructured data to make better decisions,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “This solution integrates our strengths in analytics and data with generative AI, providing users with precise answers to their questions. With Qlik Answers, we are offering a tool that supports the direct translation of unstructured data into tangible business outcomes.”
Key Benefits of Qlik Answers:
AI-Powered Responses: Delivers relevant answers from curated knowledge bases, enhancing the utility of unstructured data. Rapid Deployment: Offers a ready-to-use solution, reducing the time and complexity of deployment. Transparency: Ensures full explainability with answers linked to their source documents, fostering trust and consistency. Broad Connectivity: Integrates with existing systems and platforms, using Qlik’s enterprise connectors to access a variety of unstructured data sources. Enhanced Efficiency: Supports real-time business activities and decisions, enabling users to quickly access relevant information.
“We’re excited to see Qlik focus on unlocking business outcomes from unstructured data with Qlik Answers,” said Stefan Heinz, Senior BI & Analytics Manager at Bystronic Group. “The full explainability and integration with Qlik’s trusted analytics platform promise to drive responsible and effective use of AI at an enterprise level.”
Qlik Answers combines technologies to deliver reliable and efficient access to unstructured data. At its core, the solution uses Retrieval Augmented Generation (RAG), which merges retrieval-based and generative AI methods. This technique dynamically retrieves relevant documents from pre-indexed knowledge bases and generates precise, contextually relevant responses. By leveraging modern generative models, Qlik Answers can interpret and synthesize information from diverse sources, providing users with concise and actionable answers.
To ensure seamless integration with existing systems, Qlik Answers utilizes Qlik’s trusted enterprise connectors. These connectors allow the solution to access a wide range of unstructured data sources without requiring extensive data movement or reconfiguration. This approach not only simplifies deployment but also maintains data integrity and accessibility. Additionally, Qlik Answers is designed with full explainability and transparency in mind. All AI-generated answers are traceable back to their original sources, enabling users to verify and trust the information presented.
Qlik Answers is also self-service oriented, allowing business users to deploy and manage AI-driven knowledge assistants without needing extensive technical expertise or custom development. This ease of use ensures that organizations can quickly benefit from the solution, supporting real-time business activities and enhancing decision-making processes.
To learn more about Qlik Answers and how it can improve your business operations by unlocking the potential of unstructured data, visit Qlik Answers.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML and data management. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. Our AI/ML tools, both practical and scalable, lead to better decisions, faster. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
Source: Qlik
Qlik Introduces Qlik Answers to Transform Unstructured Data into Business Insights
PHILADELPHIA, July 30, 2024 — Qlik, a global leader in data integration, analytics, and artificial intelligence (AI), today announced the general availability of Qlik Answers, its newest self-service AI solution designed to help organizations harness the power of AI by removing the risk, embracing the complexity, and scaling the impact of AI. Qlik Answers transforms unstructured data into actionable results through generative AI, offering full explainability—a common obstacle in enterprise AI adoption.
Qlik Answers combines generative AI with Qlik’s trusted data analytics capabilities to deliver precise, contextually relevant results from extensive unstructured data sources. This solution enables customers to seamlessly integrate AI into their existing Qlik business intelligence workflows, ensuring efficient use of resources and avoiding technical debt.
“Qlik Answers is designed to help businesses use their unstructured data to make better decisions,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “This solution integrates our strengths in analytics and data with generative AI, providing users with precise answers to their questions. With Qlik Answers, we are offering a tool that supports the direct translation of unstructured data into tangible business outcomes.”
Key Benefits of Qlik Answers:
AI-Powered Responses: Delivers relevant answers from curated knowledge bases, enhancing the utility of unstructured data. Rapid Deployment: Offers a ready-to-use solution, reducing the time and complexity of deployment. Transparency: Ensures full explainability with answers linked to their source documents, fostering trust and consistency. Broad Connectivity: Integrates with existing systems and platforms, using Qlik’s enterprise connectors to access a variety of unstructured data sources. Enhanced Efficiency: Supports real-time business activities and decisions, enabling users to quickly access relevant information.
“We’re excited to see Qlik focus on unlocking business outcomes from unstructured data with Qlik Answers,” said Stefan Heinz, Senior BI & Analytics Manager at Bystronic Group. “The full explainability and integration with Qlik’s trusted analytics platform promise to drive responsible and effective use of AI at an enterprise level.”
Qlik Answers combines technologies to deliver reliable and efficient access to unstructured data. At its core, the solution uses Retrieval Augmented Generation (RAG), which merges retrieval-based and generative AI methods. This technique dynamically retrieves relevant documents from pre-indexed knowledge bases and generates precise, contextually relevant responses. By leveraging modern generative models, Qlik Answers can interpret and synthesize information from diverse sources, providing users with concise and actionable answers.
To ensure seamless integration with existing systems, Qlik Answers utilizes Qlik’s trusted enterprise connectors. These connectors allow the solution to access a wide range of unstructured data sources without requiring extensive data movement or reconfiguration. This approach not only simplifies deployment but also maintains data integrity and accessibility. Additionally, Qlik Answers is designed with full explainability and transparency in mind. All AI-generated answers are traceable back to their original sources, enabling users to verify and trust the information presented.
Qlik Answers is also self-service oriented, allowing business users to deploy and manage AI-driven knowledge assistants without needing extensive technical expertise or custom development. This ease of use ensures that organizations can quickly benefit from the solution, supporting real-time business activities and enhancing decision-making processes.
To learn more about Qlik Answers and how it can improve your business operations by unlocking the potential of unstructured data, visit Qlik Answers.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML and data management. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. Our AI/ML tools, both practical and scalable, lead to better decisions, faster. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
Source: Qlik
Exciting New Partnership: Optimum and Qlik Join Forces to Transform Data Analytics for Clients
With Seamless Data Integration and Cutting-Edge Visualization, This Partnership Will Drive Business Growth and Empower Data-Driven Decisions for Businesses of All Sizes
HOUSTON, TX / ACCESSWIRE / August 8, 2024 / Optimum Consultancy Services, a leader in IT consulting that specializes in data, business intelligence (BI), and artificial intelligence (AI) solutions, is thrilled to announce a new strategic partnership with Qlik®, a renowned leader in data integration and data analytics solutions.
This partnership is set to transform the way businesses leverage data for strategic decision-making. Through this collaboration, Optimum will integrate Qlik’s cutting-edge BI tools and data integration solutions into its service offerings. This includes the powerful Qlik Sense® platform, known for its associative analytics engine and sophisticated AI, and Qlik’s comprehensive data integration and quality solution, Qlik Talend® Cloud.
Qlik Sense® will enable Optimum’s clients to unlock powerful insights from their data, enhancing decision-making processes with interactive dashboards, fully interactive analytics apps, and beautiful reports that are accessible on any device. Additionally, the partnership will leverage Qlik’s data integration and quality to ensure that data is not only seamlessly integrated but also maintained with the highest quality and integrity. This means clients can trust the data at their fingertips, making it easier to achieve compliance with data regulations and standards.
‘We are thrilled to partner with Qlik to enhance our clients’ data integration and analytics capabilities,’ says Nooshin Yazhari, President and CEO of Optimum. ‘This partnership not only enhances our BI and AI offerings but also strengthens our data integration and quality services, ensuring our clients have access to the best tools in the industry. We are confident that our partnership with Qlik will unlock new opportunities for our clients and drive growth for their businesses.’
Benefits for Clients:
Enhanced Data Capabilities: Clients will benefit from a seamless blend of Optimum’s expertise and Qlik’s technological prowess, leading to enhanced capabilities in data processing, analytics, and decision-making.
Streamlined Operations: With improved data integration and quality, businesses can streamline their operations, reduce costs, and increase efficiency.
Competitive Advantage: By leveraging real-time data insights and forecasts, businesses can stay ahead of market trends and make informed strategic decisions that provide a competitive edge.
Scalability: The solutions provided are scalable, ensuring that as a business grows, its data solutions can grow with it without performance loss.
This strategic partnership is effective immediately, and Optimum is ready to assist businesses in implementing these powerful solutions to harness the full potential of their data.
For more information about Optimum’s partnership with Qlik, please visit our Qlik offerings page or contact us at 713.505.0300 | info@optimumcs.com.
About Optimum
Optimum Consultancy Services, based in Houston, Texas, is a leading IT consulting firm focused on delivering top-tier data and business intelligence solutions. Specializing in integrating and optimizing complex data environments, Optimum leverages cutting-edge technologies, such as Qlik, to empower clients with actionable insights and tailored analytics strategies. As a trusted advisor in the IT sector, Optimum partners with industry-leading software providers to enhance its service offerings, ensuring clients receive comprehensive, state-of-the-art support that drives significant business outcomes. Known for its commitment to excellence and innovation, Optimum continually strives to transform the data capabilities of its clients nationwide.
Learn more at www.optimumcs.com.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML and data management. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. Our AI/ML solutions, both practical and scalable, lead to better decisions, faster. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
Nooshin Yazhari President and CEO nyazhari@optimumcs.com 713.505.0300
Gabby de Janasz Marketing Specialist gdejanasz@optimumcs.com 713.505.0300
Keith Parker Senior Director, Global Corporate and Executive Communications keith.parker@qlik.com 512.367.2884
SOURCE: Optimum Consultancy Services
View the original press release on newswire.com.
Qlik Introduces Qlik Answers to Transform Unstructured Data into Business Insights
PHILADELPHIA, July 30, 2024 — Qlik, a global leader in data integration, analytics, and artificial intelligence (AI), today announced the general availability of Qlik Answers, its newest self-service AI solution designed to help organizations harness the power of AI by removing the risk, embracing the complexity, and scaling the impact of AI. Qlik Answers transforms unstructured data into actionable results through generative AI, offering full explainability—a common obstacle in enterprise AI adoption.
Qlik Answers combines generative AI with Qlik’s trusted data analytics capabilities to deliver precise, contextually relevant results from extensive unstructured data sources. This solution enables customers to seamlessly integrate AI into their existing Qlik business intelligence workflows, ensuring efficient use of resources and avoiding technical debt.
“Qlik Answers is designed to help businesses use their unstructured data to make better decisions,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “This solution integrates our strengths in analytics and data with generative AI, providing users with precise answers to their questions. With Qlik Answers, we are offering a tool that supports the direct translation of unstructured data into tangible business outcomes.”
Key Benefits of Qlik Answers:
AI-Powered Responses: Delivers relevant answers from curated knowledge bases, enhancing the utility of unstructured data. Rapid Deployment: Offers a ready-to-use solution, reducing the time and complexity of deployment. Transparency: Ensures full explainability with answers linked to their source documents, fostering trust and consistency. Broad Connectivity: Integrates with existing systems and platforms, using Qlik’s enterprise connectors to access a variety of unstructured data sources. Enhanced Efficiency: Supports real-time business activities and decisions, enabling users to quickly access relevant information.
“We’re excited to see Qlik focus on unlocking business outcomes from unstructured data with Qlik Answers,” said Stefan Heinz, Senior BI & Analytics Manager at Bystronic Group. “The full explainability and integration with Qlik’s trusted analytics platform promise to drive responsible and effective use of AI at an enterprise level.”
Qlik Answers combines technologies to deliver reliable and efficient access to unstructured data. At its core, the solution uses Retrieval Augmented Generation (RAG), which merges retrieval-based and generative AI methods. This technique dynamically retrieves relevant documents from pre-indexed knowledge bases and generates precise, contextually relevant responses. By leveraging modern generative models, Qlik Answers can interpret and synthesize information from diverse sources, providing users with concise and actionable answers.
To ensure seamless integration with existing systems, Qlik Answers utilizes Qlik’s trusted enterprise connectors. These connectors allow the solution to access a wide range of unstructured data sources without requiring extensive data movement or reconfiguration. This approach not only simplifies deployment but also maintains data integrity and accessibility. Additionally, Qlik Answers is designed with full explainability and transparency in mind. All AI-generated answers are traceable back to their original sources, enabling users to verify and trust the information presented.
Qlik Answers is also self-service oriented, allowing business users to deploy and manage AI-driven knowledge assistants without needing extensive technical expertise or custom development. This ease of use ensures that organizations can quickly benefit from the solution, supporting real-time business activities and enhancing decision-making processes.
To learn more about Qlik Answers and how it can improve your business operations by unlocking the potential of unstructured data, visit Qlik Answers.
About Qlik
Qlik converts complex data landscapes into actionable insights, driving strategic business outcomes. Serving over 40,000 global customers, our portfolio provides advanced, enterprise-grade AI/ML and data management. We excel in data integration and governance, offering comprehensive solutions that work with diverse data sources. Intuitive analytics from Qlik uncover hidden patterns, empowering teams to address complex challenges and seize new opportunities. Our AI/ML tools, both practical and scalable, lead to better decisions, faster. As strategic partners, our platform-agnostic technology and expertise make our customers more competitive.
Source: Qlik
Data Self-Service
Qlik – W&M’s data discovery tool
To meet the diverse and extensive reporting needs of the university, William & Mary uses Qlik (pronounced “Click”), a data discovery tool, to ensure effective and efficient decisions. Qlik Sense is the specific product we use to combine, analyze, and visualize institutional data.
Qlik Sense can easily extract and merge data from multiple sources, bridging gaps that previously required manual and inefficient processes. Users can search and filter data to generate an endless variety of result sets to quickly identify trends, anomalies, and aggregations vital to their day-to-day decisions. Qlik Sense supports an assortment of visualizations, including tables, bar charts, pivot tables, line charts, gauges, maps, KPIs, and many more!
Visit QLIK (QLIK.WM.EDU)
Hint: don’t download to Excel for formatting, use Qlik visualization.
Qlik App Tracker
A library of governed data exists and continues to evolve and expand. The Qlik App Tracker contains a list of Qlik Apps currently available to members of the W&M user community. Qlik App data is subject to W&M’s Acceptable Use Policy and access to a particular App is governed by its Data Steward(s).
Find My Data
Qlik Training
Ready to start using Qlik? Take the training!
Get Access to Qlik
To request new or revised access to Qlik Apps, please fill out the Qlik App Request Form. This form should be completed by the employee requesting access.
Help & Support Questions?
If you have questions after reviewing the above resources, visit support.wm.edu (select Data / Report option).
Financial Data Analysts: Making Sense of Big Data in FinTech
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Financial technology, or FinTech, data is the new gold. Companies are increasingly relying on vast amounts of data to make informed decisions, drive innovation, and maintain a competitive edge. This influx of data has given rise to a critical role within the industry: the Financial Data Analyst. These professionals are tasked with deciphering complex data sets to provide actionable insights that can shape the future of financial services.
Big Data has become a buzzword across various industries, but its impact on FinTech is particularly profound. With the proliferation of digital transactions, online banking, and mobile payments, the financial industry generates an enormous amount of data daily. This data includes everything from transaction records and customer behavior patterns to market trends and social media interactions. For FinTech companies, leveraging this data is not just a competitive advantage; it is a necessity.
However, the sheer volume, variety, and velocity of data generated in the financial sector can be overwhelming. This is where Financial Data Analysts come into play. Their expertise in data analysis helps FinTech companies navigate the complexities of Big Data, transforming it into valuable insights that drive business growth.
The Role of a Financial Data Analyst
Financial Data Analysts are the backbone of data-driven decision-making in FinTech. They possess a unique blend of financial acumen and data science skills, enabling them to interpret complex data sets and provide actionable recommendations. Their role extends beyond mere number-crunching; they are responsible for identifying patterns, trends, and anomalies that can inform strategic decisions.
Data Collection and Preparation
The first step in the data analysis process is data collection. Financial Data Analysts gather data from various sources, including transaction records, customer databases, market reports, and external data feeds. This data is often unstructured and requires significant cleaning and preprocessing before it can be analyzed. Data preparation involves removing duplicates, filling in missing values, and converting data into a structured format that can be easily analyzed.
Data Analysis and Interpretation
Once the data is prepared, Financial Data Analysts use a range of analytical tools and techniques to extract insights. This may involve statistical analysis, data mining, machine learning, and predictive modeling. The goal is to identify patterns, correlations, and trends that can inform business decisions. For example, a Financial Data Analyst might analyze customer transaction data to identify spending patterns, which can then be used to develop targeted marketing campaigns or personalized financial products.
Risk Management and Fraud Detection
One of the critical functions of Financial Data Analysts in FinTech is risk management. By analyzing historical data, they can identify potential risks and develop strategies to mitigate them. This is particularly important in areas such as credit risk assessment, where analysts use data to evaluate the creditworthiness of borrowers. Additionally, Financial Data Analysts play a crucial role in fraud detection. By analyzing transaction data in real-time, they can identify suspicious activities and flag potential fraud before it causes significant damage.
Compliance and Regulatory Reporting
The financial industry is heavily regulated, and FinTech companies must comply with various laws and regulations. Financial Data Analysts help ensure compliance by analyzing data to monitor adherence to regulatory requirements. They also assist in preparing regulatory reports, which are essential for maintaining transparency and avoiding legal penalties. In this way, Financial Data Analysts help FinTech companies navigate the complex regulatory landscape.
The Tools and Technologies Empowering Financial Data Analysts
The role of Financial Data Analysts is heavily reliant on technology. A wide array of tools and technologies are available to assist them in their tasks, from data visualization software to advanced machine learning algorithms. Below, we explore some of the key technologies that empower Financial Data Analysts in the FinTech industry.
Data Visualization Tools
Data visualization is a crucial aspect of data analysis. Financial Data Analysts use visualization tools to present complex data in a more understandable and actionable format. Tools like Tableau, Power BI, and Qlik allow analysts to create interactive dashboards, charts, and graphs that can be easily interpreted by non-technical stakeholders. These visualizations enable decision-makers to grasp insights quickly, facilitating more informed business decisions.
Machine Learning and AI
Machine learning and artificial intelligence (AI) are revolutionizing the way Financial Data Analysts work. These technologies enable analysts to automate complex tasks, such as predictive modeling and anomaly detection. For instance, machine learning algorithms can analyze vast amounts of data to predict future market trends or identify fraudulent activities in real-time. AI-powered tools also allow analysts to process unstructured data, such as text or social media posts, to gain additional insights.
Big Data Platforms
Handling Big Data requires specialized platforms that can store, process, and analyze large data sets efficiently. Financial Data Analysts often work with Big Data platforms like Apache Hadoop, Spark, and NoSQL databases. These platforms allow analysts to process massive data sets in parallel, reducing the time required for analysis. Additionally, cloud-based platforms like AWS, Google Cloud, and Microsoft Azure offer scalable solutions for storing and analyzing Big Data, making it more accessible for FinTech companies.
Programming Languages and Statistical Software
Financial Data Analysts rely on programming languages like Python, R, and SQL for data manipulation and analysis. Python and R are particularly popular due to their extensive libraries and frameworks for data science, such as Pandas, NumPy, and Scikit-learn. These languages allow analysts to perform complex statistical analyses, build predictive models, and automate repetitive tasks. SQL, on the other hand, is essential for querying and managing data in relational databases, making it a vital tool for data retrieval and preparation.
Challenges Faced by Financial Data Analysts
While the role of Financial Data Analysts is crucial, it is not without its challenges. The dynamic nature of the FinTech industry, coupled with the complexities of Big Data, presents several obstacles that analysts must overcome.
Data Quality and Integrity
One of the most significant challenges Financial Data Analysts face is ensuring the quality and integrity of the data they analyze. Incomplete, inconsistent, or inaccurate data can lead to erroneous conclusions, which can have severe implications for business decisions. Analysts must implement robust data cleaning and validation processes to ensure the data they work with is reliable and accurate.
Data Privacy and Security
With the increasing focus on data privacy and security, Financial Data Analysts must navigate the challenges of handling sensitive information. Ensuring compliance with data protection regulations, such as GDPR and CCPA, is paramount. Analysts must implement stringent security measures to protect data from breaches and unauthorized access. Additionally, they must anonymize data where necessary to protect individual privacy while still extracting valuable insights.
Keeping Up with Technological Advancements
The rapid pace of technological advancements in FinTech means that Financial Data Analysts must continuously update their skills and knowledge. New tools, techniques, and frameworks are constantly emerging, and staying ahead of the curve is essential for maintaining a competitive edge. This requires ongoing education and training, as well as a willingness to adapt to new technologies and methodologies.
The Future of Financial Data Analysts in FinTech
As the FinTech industry continues to evolve, the role of Financial Data Analysts is set to become even more critical. The increasing reliance on data-driven decision-making will drive demand for skilled analysts who can interpret complex data and provide actionable insights. Moreover, advancements in AI and machine learning will further enhance the capabilities of Financial Data Analysts, allowing them to tackle even more sophisticated challenges.
Expanding Roles and Responsibilities
The scope of Financial Data Analysts’ roles is likely to expand in the future. As FinTech companies continue to innovate, analysts may find themselves involved in more strategic decision-making processes. They may also take on additional responsibilities, such as developing and implementing data-driven strategies or advising on the adoption of new technologies. This expanded role will require analysts to possess not only technical skills but also strong business acumen and strategic thinking.
The Rise of Real-Time Data Analysis
The future of financial data analysis lies in real-time data analysis. As FinTech companies strive to offer more personalized and immediate services, the ability to analyze data in real-time will become increasingly important. Financial Data Analysts will need to leverage advanced technologies, such as streaming analytics platforms, to process and analyze data as it is generated. This will enable FinTech companies to make instant decisions and offer more responsive services to their customers.
The Integration of ESG Data
Environmental, Social, and Governance (ESG) factors are becoming increasingly important in the financial industry. As investors and regulators place more emphasis on sustainability, Financial Data Analysts will need to integrate ESG data into their analyses. This will involve assessing the impact of ESG factors on financial performance and identifying investment opportunities that align with sustainability goals. The ability to analyze and interpret ESG data will become a valuable skill for Financial Data Analysts in the future.
Conclusion
Financial Data Analysts play a pivotal role in making sense of Big Data. Their expertise in data collection, analysis, and interpretation enables FinTech companies to make informed decisions, manage risks, and stay ahead of the competition. As the industry continues to evolve, the demand for skilled Financial Data Analysts will only increase, making this an exciting and dynamic field to be a part of. With the right tools, skills, and knowledge, Financial Data Analysts are well-positioned to drive the future of financial technology and help companies navigate the complexities of Big Data.
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Global Edge Data Center Market Predicted to Cross… Business Intelligence and Analytics Fusion Introduces New AI-Powered Scenario Simulation and Intelligence Suite Fusion Risk Management (Fusion), a provider of cloud-based operational resilience, business continuity, and risk management solutions, is releasing its new Scenario Simulation and Intelligence suite—enabling companies to simulate thousands of possible scenarios against their resilience plans and strategies to identify points of weakness at scale. Posted August 14, 2024 Ridge Security Enhances Proactive Exposure Management with RidgeBot 4.3.3 Ridge Security Technology Inc. is releasing RidgeBot version 4.3.3, introducing a powerful integration that enhances proactive exposure management for organizations—combining RidgeBot’s automated vulnerability detection and validation capabilities with leading…
op Business Intelligence and Analytics Tools Organizations ‘Justice Intelligence’ Startup Darrow Expands Plaintiff-Finding Service to Mass Arbitrations On Wednesday, New York and Tel Aviv-based legal tech startup Darrow announced the addition of mass arbitration to its PlaintiffLink service. Publicly launched in February 2024, PlaintiffLink helps firms connect with and review potential plaintiffs for cases. The development and expansion of PlaintiffLink was likely supported in part by the startup’s $35 million Series B funding round, which it announced in September 2023. Marketing itself as a justice intelligence platform, Darrow essentially looks to be a business development tool for litigation teams. Some of its offerings use generative AI to analyze…
Hidden Apple Intelligence Features Revealed Hidden Apple Intelligence Features Revealed Apple’s latest iOS 18.1 beta 2 update brings a suite of advanced AI-driven features for Apple Intelligence designed to transform your user experience. These hidden gems leverage Apple’s innovative AI technology to automate tasks, enhance communication, and create personalized content, ultimately streamlining your daily interactions with your device. Let’s dive into the details of these innovative features. Smart Reply: Effortless Email and Message Responses The Smart Reply feature in iOS 18.1 takes the hassle out of responding to emails and messages. Intelligently analyzing the content of your incoming communications suggests complete, contextually relevant replies. Whether you receive…
usiness Intelligence for E-commerce KeyPoint For… True luxury is IRL E-commerce is great for a lot of things — snagging sales, stocking up on staples, buying stupid stuff we really do not need. But people’s voracious appetite for online shopping does appear to have its limits, specifically when it comes to luxury. The expectation has long been that e-commerce would revolutionize luxury, just as it has so much of retail. It killed many malls and bookstores; it made Walmart go digital; it transformed shipment and logistics operations across the globe. So why wouldn’t it disrupt such an expensive, lucrative space? It turns out we still like…
software business intelligence SAP SAP Unveils On-Demand Business Intelligence Toolset software business intelligence SAP SAP, which acquired Business Objects in early 2008, already offers hosted versions of its business intelligence tools. But the new software is SAP’s first real multi-tenant, Software-as-a-Service business intelligence application, said James Thomas, vice president of product management for SAP business intelligence tools. SAP BusinessObjects BI OnDemand ties together the vendor’s business intelligence software portfolio into a SaaS package using the BusinessObjects Explorer tool for searching and visualizing large data sets. Thomas said companies that deploy the service could expand the number of employees, particularly those in customer-facing jobs, who…
Business Intelligence vs. Competitive Intelligence Business Intelligence vs. Competitive Intelligence: What’s the Difference? Business Intelligence vs. Competitive Intelligence: An Overview Competitive intelligence is the act of understanding a company’s industry and industry rivals so the company can make better business decisions. Business intelligence refers to the tools, software, and systems that play a vital role in the strategic planning process of a company. Key Takeaways Competitive intelligence is the outward-focused analysis of a business’s competitors to identify advantages and potential strategies.In contrast, business intelligence is the inward-focused evaluation of the business’s own data, which can help improve efficiency and growth.Combining both business and competitive intelligence…
22nd Century Technologies Buys TreasurySoft 22nd Century Technologies Buys TreasurySoft to Expand ERP Capabilities for Federal Market Clients McLean, Virginia-based 22nd Century Technologies Inc. has acquired TreasurySoft in a transaction that expands its enterprise resource planning practice and capabilities to deliver digital transformation platforms to federal, state, local government and transit agencies. TSCTI said Tuesday TreasurySoft provides PeopleSoft and Oracle Fusion ERP Treasury Management Systems and other tech platforms that offer real-time insights across cash management, risk management, investment management and other critical financial functions. “By bringing TreasurySoft into our fold, we are not only expanding our ERP capabilities but also setting the stage to…
How Zebra Technologies Uses Machine Vision to… How Zebra Technologies Uses Machine Vision to Transform Production Automation Machine vision is the focus of Machine Design’s Takeover Topic Event (Aug. 12-16, 2024). Covering the gamut of vision systems, the lineup includes case histories, trends and interviews with notable players to watch in this space. In the accompanying video, Andrew Zosel, senior vice president and general manager, Zebra Technologies, explains the vision and strategy behind recent acquisitions and the resultant solutions. Machine vision is a significant part of that investment and future growth at Zebra, said Zosel. (In parts 2 and 3 of this interview series focusing on machine…
SEALSQ Unveils Revolutionary Artificial Intelligence… SEALSQ Unveils Revolutionary Artificial Intelligence for Internet of Things (AIoT) Strategy, Pioneering the Future of Connected Intelligence Geneva, Switzerland, Aug. 14, 2024 (GLOBE NEWSWIRE) — SEALSQ Corp (NASDAQ: LAES) (“SEALSQ” or “Company”), a company that focuses on developing and selling Semiconductors, PKI and Post-Quantum technology hardware and software products, announces its bold entry into the AI chip market, underscored by its visionary AIoT (Artificial Intelligence for Internet of Things) strategy, which seamlessly merges the power of AI with the expansive potential of IoT technologies. This move positions SEALSQ at the cutting edge of technological innovation, where the convergence of AI…
Business Intelligence in ERP (The Role of BI Tools in ERP) De-siloing the enterprise: The challenges and opportunities in data consolidation A hot topic in the data management space is the argument against data silos. Factors such as generative artificial intelligence and decentralized data infrastructures have intensified the need to embrace the data consolidation ethos. RelationalAI’s Molham Aref discusses modern data platforms. What is the imperative to de-silo data operations? And what challenges and opportunities exist as companies move toward interconnected data infrastructures? “You’re building intelligent applications, and by definition, these applications have to look at data,” said Molham Aref (pictured), chief executive officer of RelationalAI Inc. “The old architecture is where…
Snowflake launches Cortex Analyst, an agentic AI… Snowflake launches Cortex Analyst, an agentic AI system for accurate data analytics Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Snowflake is all set to deploy powerful language models for complex data work. Today, the company announced it is launching Cortex Analyst, an all-new agentic AI system for self-service analytics, in public preview. First announced during the company’s data cloud summit in June, Cortex Analyst is a fully managed service that provides businesses with a conversational interface to talk to their data. All the users have to do is…
Common Mistakes to Avoid When Hiring a Power BI Developer Common Mistakes to Avoid When Hiring a Power BI Developer Businesses depend intensely on information analytics to make informed decisions, and Power BI has risen as a prevalent tool for turning raw data into significant insights. Hiring a Power BI engineer is a crucial choice that can altogether affect your organization’s victory. In any case, companies frequently make a few mistakes when hiring Control BI engineers that can lead to project delays, destitute results, and unnecessary costs. Here are five common mistakes businesses make when hiring Power BI developers and we offer significant tips to avoid them. Common mistakes when…
Magic Quadrant for Analytics & Business Intelligence… Gartner says everyday AI and digital employee experience are two years away from mainstream adoption ERROR: The request could not be satisfied Request blocked. We can’t connect to the server for this app or website at this time. There might be too much traffic or a configuration error. Try again later, or contact the app or website owner. If you provide content to customers through CloudFront, you can find steps to troubleshoot and help prevent this error by reviewing the CloudFront documentation. Generated by cloudfront (CloudFront) Request ID: GFd0flXaeUjYUvECGjo3GIRU7HEI9EgAwOe2IsvR7iPvJ1p9qTAa3A== Gartner says everyday AI and digital employee experience are two years…
Business Intelligence Platforms: Best Analytics & BI… How Women Business Owners Are Using Artificial Intelligence Written by Lesa Seibert, NAWBO National Board Secretary, member of NAWBO Kentucky and CEO of Mightily The intersection of artificial intelligence and public policy has been at the forefront this past year since President Biden issued an executive order on AI that provides entrepreneurs with access to technical assistance and resources, among other things. Senate Majority Leader Chuck Schumer followed up the executive order with a series of AI Insight Forums to discuss the intersection of AI and innovation, workforce and intellectual property issues. As the governance of AI continues to take…
Common Mistakes to Avoid When Hiring a Power BI Developer Common Mistakes to Avoid When Hiring a Power BI Developer Businesses depend intensely on information analytics to make informed decisions, and Power BI has risen as a prevalent tool for turning raw data into significant insights. Hiring a Power BI engineer is a crucial choice that can altogether affect your organization’s victory. In any case, companies frequently make a few mistakes when hiring Control BI engineers that can lead to project delays, destitute results, and unnecessary costs. Here are five common mistakes businesses make when hiring Power BI developers and we offer significant tips to avoid them. Common mistakes when…
Google keeps scaling back AI search results, new study finds Google keeps scaling back AI search results, new study finds Google’s AI Overviews in search results have dropped off significantly in recent months, according to a new study. The search giant is rethinking how it uses artificial intelligence in its biggest product. Researchers at SE Ranking have been closely tracking how often Google’s AI-generated responses appear in results and the sources the tool cites. In a test of around 100,000 searches on Google conducted in July, just 7.47% produced an AI Overview, which was a 1.24% drop from the previous month, the researchers found. That’s also a huge fall-off from…
Meta scraps celebrity AI chatbots after less than a year Artificial Intelligence Tech 2024-08-13T18:31:05Z Replika lets you buy an AI girlfriend or boyfriend — and its average user age is surprising Replika CEO Eugenia Kuyda said the app’s users are “mostly 35-plus and super engaged.” Some people have formed deep bonds with their AI companions. Tech 2024-08-13T13:40:11Z AI and security concerns fuel a shift to on-premises IT infrastructure as companies seek more control of data AI, data privacy, and security concerns are pushing companies to adopt hybrid IT infrastructure that combines on-prem hardware with cloud services. Business Intelligence PowerPoint Template PPT Templates The US and some of its allies just…
How to create Excel dashboards with Claude How to create Excel dashboards with Claude 3 AI in minutes If you are looking for a fast and efficient way to create Excel dashboards to present your data in presentations or reports. You might be interested to know that you can use the power of Claude 3 AI to help create these Excel interactive dashboards just a few minutes. Saving you hours of time which can be spent more wisely. Creating interactive dashboards has become an essential skill and by using Claude 3 AI, a powerful artificial intelligence tool, this process has been streamlined and simplified. This guide created…
The Microsoft Dynamics 365 CRM is excellent Microsoft Dynamics vs. Salesforce: Comparison 2024 Salesforce vs. Microsoft Dynamics 365 Overview Salesforce’s Sales Hub and Microsoft Dynamics 365 Sales are similar products that offer most of the CRM features you expect to find in standalone CRM software. We compare these two as the primary CRM offerings from both providers, though other products exist for marketing, customer service and other work management functions. Salesforce is a highly customizable CRM that teams can configure for almost any business need, while Microsoft Dynamics 365 serves as a centralized place for customer data for teams that already use it. Salesforce vs. Microsoft Dynamics…
How Gen Z Is Changing Business and the Workplace Microsoft to reinvent office apps with Artificial Intelligence toolsWashington [US], March 17 (ANI): Microsoft is reinventing its Power Platform’s software development, including Outlook, PowerPoint, Excel and Word, with AI-powered no-code development and adding new features like Copilot. In an event on Thursday (Local Time), the company announced that Microsoft 365 users will soon be able to use what the company is calling an AI “Co-pilot,” Microsoft said in a statement. “Makers now have a live in-studio copilot that helps them build solutions and provides suggestions for improvement. To build an app, flow, or bot, you can describe it using natural…
Smart Automation: AI’s Impact On Operational Efficiency Smart Automation: AI’s Impact On Operational Efficiency Atal Bansal is the Founder and CEO at Chetu, a global U.S.-based custom software solutions and support services provider. getty AI “smart” or “intelligent” automation seems unstoppable because it promises to save money, minimize human error, and produce faster results. The impact on workers and the workplace will be dramatic. Business Intelligence: making Smart Business Decisions Goldman Sachs reports that “two-thirds of occupations could be partially automated by AI.” McKinsey echoes this sentiment in an article: “Current generative AI and other technologies have the potential to automate work activities that absorb 60 to…
54 Predictions About The State Of Data In 2021 54 Predictions About The State Of Data In 2021 From 2010 to 2020, the amount of data created, captured, copied, and consumed in the world increased from 1.2 trillion gigabytes to 59 trillion gigabytes, an almost 5,000% growth. What will data do in the coming decade? Happy New Year! getty 26 the five-year compound annual growth rate (CAGR) through 2024 of the data created, captured, copied, and consumed in the world; the amount of data created over the next three years will be more than the data created over the past 30 years [IDC] ⦨ Richard van Dijk ⦩ LinkedIn 22 the…
Microsoft Dynamics vs. Salesforce: Comparison 2024… Microsoft Dynamics vs. Salesforce: Comparison 2024 Salesforce vs. Microsoft Dynamics 365 Overview Salesforce’s Sales Hub and Microsoft Dynamics 365 Sales are similar products that offer most of the CRM features you expect to find in standalone CRM software. We compare these two as the primary CRM offerings from both providers, though other products exist for marketing, customer service and other work management functions. Salesforce is a highly customizable CRM that teams can configure for almost any business need, while Microsoft Dynamics 365 serves as a centralized place for customer data for teams that already use it. Salesforce vs. Microsoft Dynamics…
RBC Capital Keeps Their Buy Rating on Jasper… RBC Capital Keeps Their Buy Rating on Jasper Therapeutics (JSPR) In a report released yesterday, Gregory Renza from RBC Capital maintained a Buy rating on Jasper Therapeutics (JSPR – Research Report), with a price target of $68.00. The company’s shares closed yesterday at $18.85. Renza covers the Healthcare sector, focusing on stocks such as Perspective Therapeutics, Pacira Pharmaceuticals, and Viridian Therapeutics. According to TipRanks, Renza has an average return of 13.8% and a 45.27% success rate on recommended stocks. Jasper Therapeutics has an analyst consensus of Strong Buy, with a price target consensus of $72.71, which is a 285.73% upside…
Salesforce vs. Microsoft Dynamics 365 Overview Microsoft Dynamics vs. Salesforce: Comparison 2024 Salesforce vs. Microsoft Dynamics 365 Overview Salesforce’s Sales Hub and Microsoft Dynamics 365 Sales are similar products that offer most of the CRM features you expect to find in standalone CRM software. We compare these two as the primary CRM offerings from both providers, though other products exist for marketing, customer service and other work management functions. Salesforce is a highly customizable CRM that teams can configure for almost any business need, while Microsoft Dynamics 365 serves as a centralized place for customer data for teams that already use it. Salesforce vs. Microsoft Dynamics…
