Tag Archives: Trends

Hive 2.0 – The Solution For Data Warehousing

Slides from presentation by Hortonworks’ founder Alan Gates describing at high-level new features of Hive 2.0 tailored for the kind of queries typical for Data Warehousing: Apache Hive 2.0: SQL, Speed, Scale from Hadoop Summit Hive with LLAP is available … Continue reading

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BIModal IT: Unheeded Silver Bullet?

Gartner gives the next definition for it’s new Bimodal approach: The essence of an enterprise bimodal capability is marrying more predictable evolution of products and technologies (Mode 1) with the new and innovative (Mode 2): Mode 1 is optimized for … Continue reading

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Governed Data Discovery vs BI

Governed Data Discovery vs BI: Is there the best strategy? Governed Data Discovery is one of the trending buzzword since 2014. The term made its debut in Gartner’s 2014 Magic Quadrant Report. Gartner first popularized the term data discovery and … Continue reading

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Smart Data – Extracting Quality From Quantity

Amit Sheth defined “Smart Data” as “realising productivity, efficiency, and effectiveness gains by using semantics to transform raw data into Smart Data.” Clarifying “Smart Data” concept can be understood as automation of the process represented by the arrow linking “Information” and … Continue reading

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From SQL to NoSQL to NewSQL

History of RDBMS Every time new technology emerged it’s evolution ended up in realisation as relational system (RDBMS). In other words, the business before adopting the stuff always demanded atomicity, consistency, isolation, and durability (ACID).

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SQL or NoSQL: that is the question.

Relational database management system (RDBMS) have been a primary data storage mechanism for decades. NoSQL databases have existed since the 1960s, but have been recently gaining traction and the business faces a challenge of their efficient adoption. There are many tutorials … Continue reading

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Hadoop Data Processing: Battle For Speed

The idea behind Hadoop шs brilliant and revolutionary: invented an algorithm – MapReduce – allowing decomposition on it of all major data processing tasks (grouping, statistical, graph, etc). However it’s use of input files and lack of schema support prevented the performance improvements … Continue reading

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