Big data analytics is about applying advanced methods and technologies to derive insights from very large and diverse data sets that often include varied data types and streaming data. This TDWI Checklist Report discusses steps for realizing value from big data and analytics for better customer intelligence.
Sponsored By Datawatch, SAS, Teradata, Treasure Data
From in-memory databases to big data, from unstructured data to geospatial data, the enterprise data warehouse is facing impacts from a variety of technologies. Get an insider's look into the next generation of BI in this TDWI E-Book.
Sponsored By SAP
Tools from new vendors incorporating new big data technologies (such as Hadoop) for distributed and parallel computing and NoSQL data management are rapidly being evaluated and brought into
organizations. At the same time, numerous vendors of traditional platforms are offering the same or similar new technologies that are more robust and have more enterprise-ready capabilities than the new technologies can provide. This Checklist Report offers several important items to consider for your data management infrastructure, whether your implementation is on-premises, in the cloud, or a hybrid.
Sponsored By IBM
Without accurate and trustworthy data, the value of enterprise analytics will be diminished. This TDWI E-Book describes the value of confidence in your data, and how to get it.
Put the customer first. The customer is king. Keep the customer satisfied. Those
familiar adages ring especially true in this issue of the Business Intelligence Journal.
Master data management (MDM) can be practiced many different ways, with various user conventions and a broad array of vendor-built technologies. However, this report focuses on a specific practice called unified MDM, and examines the characteristics typical of business programs and technical solutions for unified MDM.
Sponsored By SAS
By Fern Halper
This Ten Mistakes to Avoid covers what works and doesn’t work when it comes to big data analytics projects.
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