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Fire Your Super-Smart Data Consultants with DataOps

DataKitchen

When internal resources fall short, companies outsource data engineering and analytics. There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

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DataOps For Business Analytics Teams

DataKitchen

A DataOps process hub offers a way for business analytics teams to cope with fast-paced requirements without expanding staff or sacrificing quality. Analytics Hub and Spoke. The data analytics function in large enterprises is generally distributed across departments and roles. Business Analytic Challenges.

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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

HR&A Advisors —a multi-disciplinary consultancy with extensive work in the broadband and digital equity space is helping its state, county, and municipal clients deliver affordable internet access by analyzing locally specific digital inclusion needs and building tailored digital equity plans.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. This analytics function is so crucial to product success that the data team often reports directly into sales and marketing. The Otezla team built a system with tens of thousands of automated tests checking data and analytics quality.

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Decoding Data Analyst Job Description: Skills, Tools, and Career Paths

FineReport

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

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The Madness of Data (and analytics) Governance

Andrew White

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata.