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“Data Wrangling” = Data Rankled

Data wrangling is the latest clever way to describe the lengthy and cumbersome data preparation process required to make modern complex data (aka: post-relational, multi-structured, semi-structured…) fit legacy (read: relational) analytics tools.

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Wise Up NoSQL!

SQL was the glue that held together the relational database market for the past 40+ years. More importantly SQL allowed it to thrive as an ecosystem. Solutions like Business Intelligence (BI), Data Warehousing, and RDBMS management tools would not have been possible without the Lingua Franca.

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B2B SaaS Breakthrough: Scale Secure Dashboards On MongoDB For Your Clients

If you’re reading this, then you’re in the know. You know that MongoDB’s “flexibility” around data models kicked the doors down and ushered in a brave new world of software development. Development is now exponentially faster, easier and cheaper to build. And MongoDB has moved beyond cloud-based consumer apps and is now no doubt running in production environments in government, healthcare, industrial, energy — really all over the enterprise.

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New Edition of SlamData 2.5 Will Add Enterprise Level Feature Set

SlamData, Inc., commercial developer of the SlamData open source project, today announced Q1 2016 availability of an advanced edition of the NoSQL analytics application. The announcement was made at MongoDB Days SV, MongoDB’s west coast conference being held at the San Jose Convention Center on December 2. SlamData is a presenting sponsor for the event.

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Database Wars 2.0 (Part 1)

For old guys like me (I started my career in tech in 1987) we remember well the “Database Wars” of the late 80’s and early 90’s. Oracle, Sybase, Informix and DB2 battled for database supremacy. Newsflash, Oracle won.

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Why Modern BI is Failing

Legacy BI tools were not built to handle modern NoSQL data models like JSON or XML. Change starts with real innovation, not tweaking the status quo.

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Are You Drowning In The Data Lake?

The Hadoop Data Lake has been positioned as the one size fits all answer to a company’s data silo problems. In reality, Hadoop is often NOT the most efficient answer to the problem.

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