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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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A comparative assessment of digital transformation in Italy

CIO Business Intelligence

Finally, the flow of AMA reports and activities generates a lot of data for the SAP system, and to be more effective, we’ll start managing it with data and business intelligence.”

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Demystifying Modern Data Platforms

Cloudera

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The high-level architecture shown below forms the backdrop for the exploration. Luke: Let’s talk about some of the fundamentals of modern data architecture.

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Decades of empowering efficient data decisions

IBM Big Data Hub

As a company, we have been entrusted with organizing data on a national scale, made revolutionary progress in data storing technology and have exponentially advanced trustworthy AI using aggregated structured and unstructured data from both internal and external sources. .

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What is a data engineer? An analytics role in high demand

CIO Business Intelligence

Data engineers and data scientists often work closely together but serve very different functions. Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data engineer vs. data architect.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

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The New Normal for FP&A: Data Analytics

Jedox

Gartner defines “dark data” as the data organizations collect, process, and store during regular business activities, but doesn’t use any further. Gartner also estimates 80% of all data is “dark”, while 93% of unstructured data is “dark.”.