Extract, transform and load (ETL) is a core process of data integration in which data is extracted from a chosen source(s), transformed into new formats according to business rules, and loaded into target data structure(s).


NewsYears in the making, in-memory platform for Hadoop attempts to make wider and quicker business use of big data; ESG and Taneja analysts note strong potential
BlogOrganizations diving into hype now struggling with data movement, access
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BlogWith other trends at the door, 2013 may be crucial for clean enterprise info
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ColumnBy systematically assessing the key drivers of solution design, you can determine the solution that will truly align with your business needs, in spite of more choices and more users
FeatureA shift in data architecture has led to a new data warehousing process, as the previous data models were not equipped to handle the exponential increase in user data
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blogStrata Hadoop World spanned a range of analytics innovation and hype
columnA serious problem is that there seems to be no common agreement on what the dimensions of data quality actually are
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Data integration efforts can expose a lot of other underlying information issues, not to mention some groaning from IT officers. Even with more data coming from more sources than ever before, there are a few basic data integration principles that can keep your implementation from going haywire.
newsU.K. storage and migration tools vendor would move into IBM’s Software Group; deal proposed for undisclosed amount
blogIn part 3 of a series, a reboot on data purging and quality
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newsToad BI Suite is the first analytics software from database regular; ESG analyst sees a direct pool of users, even among BI crowd
commentaryWe witness a tendency with IT managers to treat data testing the old-fashioned way: hiring second-class resources and wasting excessive man-hours on repetitive and manual processes that could have otherwise gone into more impactful quality assurance
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Where do young IT professionals (30 and under) obtain information to aid with daily role responsibilities and career development?

Trade publication websites 14%
Social media 23%
Vendor websites 4%
Vendor/community forums 7%
Newsletters 1%
Trade conferences/meetups 2%
RSS feeds 6%
Web search 44%

 

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