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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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Decoding Salesforce’s plausible $11 billion bid to acquire Informatica

CIO Business Intelligence

Salesforce’s reported bid to acquire enterprise data management vendor Informatica could mean consolidation for the integration platform-as-a-service (iPaaS) market and a new revenue stream for Salesforce, according to analysts. The enterprise data management vendor reported a total revenue of $1.5 billion and $1.6

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

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Data integrity vs. data quality: Is there a difference?

IBM Big Data Hub

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

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Introducing The Five Pillars Of Data Journeys

DataKitchen

Our recent survey showed that 97% of data engineers report experiencing burnout in their day-to-day jobs. The spiritual benefits of letting go may be profound, but finding and fixing the problem at its root is, as Samuel Florman writes, “ existential joy.” Failures on the Data Journey cost organizations millions of dollars.

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Don’t let your data pipeline slow to a trickle of low-quality data

IBM Big Data Hub

Businesses of all sizes, in all industries are facing a data quality problem. 73% of business executives are unhappy with data quality and 61% of organizations are unable to harness data to create a sustained competitive advantage 1.

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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.