DATA MANAGEMENT INSIGHTS
Turn big data into big value
Recent Data Management articles
- 5 data management best practices to help you do data rightFollow these 5 data management best practices to make sure your business data gives you great results from analytics.
- The transformational power of evidence-based decision making in health policyState health agencies are under pressure to deliver better health outcomes while minimizing costs. Read how data and analytics are being used to confront our biggest health care challenges head on.
- IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
- Data lineage: Making artificial intelligence smarterFor AI to reach its full potential, the data feeding its algorithms and models needs to be well-understood. Data lineage plays a vital role in understanding data, making it a foundational principle of AI.
- Key questions to kick off your data analytics projectsThere’s no single blueprint for starting a data analytics project. Technology expert Phil Simon suggests considering these ten questions as a preliminary guide.
- 5 ways to become data-drivenSuccessful data-driven businesses foster collaborative, goal-oriented cultures, have leaders who believe in data and are governance-oriented. Read more in this summary of TDWI research that uncovers best practices for becoming data-driven.
- The five D's of data preparationFrom discovering which data is best to use, to delivering it in the right format to users, learn why these 5 D’s are essential to data preparation.
- Data management backgrounderFrom data integration to data quality and data preparation, find out what these terms mean and why they’re so important for your analytics projects.
- Data lake and data warehouse – know the differenceData lake – is it just marketing hype or a new name for a data warehouse? Find out what a data lake is, how it works and when you might need one.
- What is data profiling and how does it make big data easier?Data profiling, the act of monitoring and cleansing data, is an important tool organizations can use to make better data decisions.
- Three C’s of the connected customer in the IoTTo optimize the connected customer experience, Blue Hill Research says organizations should build an IoT model based on three key features.
- 5 steps to sustainable GDPR complianceFollow these steps to achieve GDPR compliance by the May 2018 deadline – and get added benefits along the way.
- General Data Protection Regulation: From burden to opportunityThe General Data Protection Regulation stirs up mixed emotions, but Kalliopi Spyridaki shows how to use the new legislation for business advantage.
- How openness can supercharge event stream analyticsWhat does openness do for event stream analytics? David Loshin shows how it helps you speed and govern the full streaming analytics life cycle.
- IoT success depends on data governance, security and privacyThe IoT puts intense demands on the data management life cycle. Learn from 10 common mistakes organizations have made with IoT endeavors.
- How to improve data prep for analytics: TDWI shares best practicesGetting good results from your data means doing a good job of preparing the data for analytics. Find out what TDWI says it takes to get there.
- Big data privacy: Four ways your data governance strategy affects security, privacy and trustWith IT and business strategies converging, something that’s a little late to the party is the concept of big data privacy.
- 5 ways data monetization can inform data strategyData monetization promises more than monetary returns. Anne Buff explains how monetization drives strategy for data-driven organizations.
- Data management for cybersecurity: Know the essentialsSecurity teams tend to underestimate the importance of data management for cybersecurity. See the seven key reasons data management has been so difficult and five steps to getting it right.
- Tips for successful data integration modernizationOrganizations today have to capture, process and move all types of new and big data. Get some tips for data integration modernization from TDWI.
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