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A step-by-step guide to setting up a data governance program

IBM Big Data Hub

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

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Automate discovery of data relationships using ML and Amazon Neptune graph technology

AWS Big Data

The goal of a data product is to solve the long-standing issue of data silos and data quality. Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights.

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Top 6 Benefits of Automating End-to-End Data Lineage

erwin

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. However, different types of data need to be treated differently.

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The Chief Marketing Officer and the CDO – A Modern Fable

Peter James Thomas

Prelude… I recently came across an article in Marketing Week with the clickbait-worthy headline of Why the rise of the chief data officer will be short-lived (their choice of capitalisation). It may well be that one thing that a CDO needs to get going is a data transformation programme. It may be to improve Data Quality.

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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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Breaking down data silos for digital success

CIO Business Intelligence

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

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Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh. Once accomplished, an effective implementation spurs a mindset in which organizations prioritize and value data for decision-making, formulating strategies, and day-to-day operations.