Category Archives: Big Data
One of the tasks of Database Forensics is to detect events (or categories of events) that began too frequent. From programming perspective, this means that for each date there should be searches categories appearing more than certain number of times … Continue reading
Two competing cloud storage products by Microsoft are defined the next way: Azure Blob Storage is a general purpose, scalable object store that is designed for a wide variety of storage scenarios. Azure Data Lake Store is a hyper-scale repository that … Continue reading
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
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
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
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).
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