Data Architecture

Data architecture is a formal description and mapping of the plan and structure of data assets used to support organizational goals. Components of data architecture include the databases, stores, and the integration by which data is defined, flows, is accessed and understood in current and future states for organizational purposes.

Which big data companies generate the most revenues? Wikibon analyzed the players based on sales from hardware, software and related IT services.
If you’re on the market for a top shelf master data management solution, this newly-released listing from The MDM Institute offers great insights on products you should include in your search.
This year has seen tremendous changes in the areas of analytics, machine learning, and the Internet of Things. Expect more of the same in 2017, according to these experts.
Organizations are increasingly looking to simplify their data architecture and decrease the time to value from data. But there are a number of challenges in selecting the right data management platform to manage multiple data streams. Here are the top 5 roadblocks.
FeatureDespite all the attention paid to big data and data management, many organizations continue to struggle with getting full value from their data assets.
newsComputer science researchers have developed a visual cloud computing architecture that streamlines the process of providing first responders with visual data created by security cameras, personal mobile devices and aerial video.
Spending on information technology is on the increase in the government sector this year, and that includes a significant portion toward data management and data analytics related issues. This week research firm Gartner Inc. released its report on “The Top 10 Strategic Technology Trends for Government in 2016.”
FeatureDifferent levels of the stack, including storage, database, clustering, data flow, data processing, analytics, and messaging are all composed together to form the final product.
There seems to be no end in sight when it comes to high demand for data professionals. But just how well an individual can cash in on that trend depends on their job experience, location, and acquired skills. This week we look at how all those factors impact the paycheck. Today we review the pay premiums being paid in 2016 for the top noncertified data skills.
Data professionals continue to be among the most in-demand in the job market, but what they earn -- or you should be paying -- depends on industry experience, location, technical skills, and contribution to the bottom line. This week we look at how data professionals can earn top dollar, depending on job focus, certifications earned, and skill concentrations. In part one we look at the top paying data certifications.
FeatureMany organizations have complete phase one of their data analytics initiatives – the implementation phase – and now want real actionable results, says Tim Rizzi of DataScience.
NewsSelf-service data preparation is one of the key components in an effective analytics strategy, the Bedford, MA-based firm noted in its announcement.
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