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
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
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
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
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.
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.
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.
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.
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
We hear more and more about semantics these days, but what does it mean? What is an ontology and how does it relate to a data model? Do semantics and ontologies have a role to play in data architecture and data modeling?
April 12, 2018
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
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
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
You need a powerful, simple, and affordable data warehouse built for the cloud to store and analyze all your data in one location. In this e-book, we’ll detail key insights you can use to champion modern data warehouse technology within your organization, helping it become a data-driven enterprise.
February 14, 2018
This brief white paper, by leading industry analyst firm Enterprise Management Associates (EMA), provides advice on using embedded analytics to provide better strategic planning, increased visibility across your organization, and quicker time to value.
April 10, 2018
Small to medium-sized businesses use, on average, fifteen SaaS applications to boost productivity and open new engagement channels with customers. Download this white paper to see how data pipeline automation can give these companies a huge competitive advantage.
April 9, 2018
TDWI’s Best Practices Awards program is designed to identify and honor companies and other organizations that have demonstrated best practices in developing, deploying, and maintaining solutions.
5 Reports to Help you Prepare for the Future of Analytics
Data Management for Next-Generation Analytics
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