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TDWI Upside - Where Data Means Business

Data Lakes and Data Storage

How Customers Drive BI and Analytics Innovation

The upcoming TDWI Executive Summit in San Diego will explore innovations in BI, analytics, and data management that are essential for achieving customer intelligence and better customer experiences.

Data Digest: Choosing Data Storage, Managing Big Data, BI Basics

In these articles, read the pros and cons of choosing a data lake versus a data warehouse, learn how to manage the growing flood of data, and understand the basic principles and tools of modern BI.

SQL, NoSQL, or Hadoop? Determining the Best Platform for Your Purpose

An increasing variety of data types, analytics needs, and business uses drive data architecture decisions today. Follow this real-world, informal evaluation of SQL, NoSQL, and Hadoop solutions that address a business use case.

Data Digest: Big Data Solutions, Content Marketing Analytics, Enterprise-Ready Data Lakes

Today read tips for choosing the right big data solution, using predictive analytics to improve your content marketing, and building an enterprise-ready data lake.

Data Digest: Analytics Detects Plagiarism, ROI on Data Lakes, Cloud Adoption Tips

Read today about the crossword plagiarism scandal revealed by analytics, how to make back your investment in data lake technology, and best practices for adopting cloud computing.

Data Digest: Unlocking Data Lake’s Value, Mining Excess Big Data, Cloud Computing Myths

Learn ways your data lake can reach its full potential, explore profitable uses for unused data, and popular myths about cloud computing busted.

Q&A: Emerging Tech Trends Pave Path to Integration-Platform-as-a-Service

With the continuing push for more speed and for cloud offerings, integration platform-as-a-service is gaining traction in new ways.

Data Digest: Big Data Context, Data Lake in a Box, Data Governance Mistakes

Read how KPIs give necessary context to big data, how Koverse promises an effective data lake in 30 days, and what 5 data governance mistakes to avoid in your big data project.

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Individual, Student, & Team memberships available.