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This first in a new series of reports offers focused research and analysis of trending analytics, business intelligence, and data management issues facing organizations. TDWI Pulse Reports are designed to educate technical and business professionals and aid them in developing strategies for improvement. March 29, 2018 Read Now
Users ignore the modernization of deep warehouse infrastructure at their peril. Without it, they may achieve complete, clean, and beautifully modeled data, but without the ability to scale to big data, iterate data models on the fly, enable flexible self-service access, operate continuously and in real-time (as warehouses must in global businesses), and handle new data types and workflows for advanced analytics. March 30, 2018 Read Now
The foundation of a successful IoT implementation is a technical architecture that blends network connectivity with an information architecture for streaming, ingesting, filtering, and capturing data. This checklist explores some fundamental aspects of the data architecture necessary for IoT success. March 30, 2018 Read Now
As organizations collect and analyze increasing amounts of data, they are turning to the data lake as the platform to perform more advanced analytics such as machine learning. This TDWI Checklist Report presents best practices for advanced analytics on a data lake. March 30, 2018 Read Now
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The TDWI Self-Service Analytics Maturity Model Guide is designed to help you understand the phases of maturity in self-service analytics, interpret your assessment scores, and provide best practices to move you forward. Its insight and advice can help you quickly advance your self-service analytics initiatives to gain more value. Read Now
The Internet of Things (IoT)—a network of connected devices that collect and interpret data over the Internet—is a hot and growing trend. These devices—which include sensors, RFID tags, and more—are in your home in smart appliances; you’re wearing them for health and wellness. They are on factory floors, in office buildings, on farms, and much more. IoT is being used by organizations to change their business model, improve operations, and improve the customer experience. Some view it as a competitive necessity. Read Now
TDWI has developed an analytics maturity model to help you determine the maturity of your organization's analytics initiatives when compared with other companies. The model provides the big picture of an analytics program, where it needs to go, and where you should concentrate your attention to create more value for your data. Read Now
TDWI's Hadoop Readiness Assessment is an online questionnaire that asks how prepared you and your organization are to get full value from Hadoop. When you complete the questionnaire, the assessment tool immediately shows you scores that quantify your readiness for Hadoop. It is designed to help answer your questions about where to focus your best efforts with Hadoop. Read Now
Businesses can only seize new data-driven opportunities if they recognize sensitive data and handle it responsibly. This report focuses on how targeted improvements to specific data management best practices and technology can contribute significantly to your success with GDPR compliance, as well as data governance and data-driven programs in general. March 6, 2018 Read Now
The deadline for complying with the European Union’s General Data Protection Regulation (GDPR) is fast approaching. The EU calls it “the most important change in data privacy regulation in 20 years” – and that’s no exaggeration. Beginning May 25, 2018, organizations that are in non-compliance may face heavy fines, not to mention damage to their reputations. How does this regulation affect the way your organization uses data for analytics and business intelligence? What do you need to do from a data management perspective to ensure compliance – not just by May 25, but into the future? April 30, 2018 View Now
Analytics has become mainstream, and TDWI research indicates that the vast majority of organizations have adopted technologies such as dashboards and visual analytics. However, as organizations mature along their analytics journey, they are looking to embed their analytics into devices, applications, and systems. Embedding analytics layers analytics into another application or process and brings the results of analysis to the decision maker through applications that run the business. The result is opening up analytics to more users and making analytics relevant, actionable, and more valuable. May 30, 2018 View Now
However, embracing machine learning successfully is challenged by ML’s serious data requirements. In development, designing an analytic model depends on very large volumes of diverse data. In production, an analytic model created via machine learning again needs voluminous data, so it can learn and improve over time. In turn, managing big data for machine learning demands a substantial data management infrastructure and tool portfolio. May 31, 2018 View Now
More than 90% of participants in our research said that IoT is important to their future operations. Download this white paper to learn how to extract the value from IoT data and analytics. April 1, 2018 Read Now
If you want your business to be data-driven, you must first make an important decision about how to tap into your organization’s vast resources of raw data and how to turn this data into actionable business intelligence. March 9, 2018 Read Now
It can be hard to keep up with the rapidly changing business intelligence (BI) landscape. But it doesn't have to be. April 23, 2018 Read Now
Modern BI solutions can increase the value of big data exponentially by lowering the barrier to entry with user-friendly solutions. April 23, 2018 Read Now
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5 Reports to Help you Prepare for the Future of Analytics
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