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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

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5 surefire ways to derail a digital transformation (without knowing it)

CIO Business Intelligence

Having too many number-one priorities sets unrealistic expectations with business stakeholders and stresses team leaders. Worse is when prioritized initiatives don’t have a documented shared vision, including a definition of the customer, targeted value propositions, and achievable success criteria.

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Accomplish Agile Business Intelligence & Analytics For Your Business

datapine

When encouraging these BI best practices what we are really doing is advocating for agile business intelligence and analytics. Therefore, we will walk you through this beginner’s guide on agile business intelligence and analytics to help you understand how they work and the methodology behind them.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data. Data Quality.

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing.

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Your Data Won’t Speak Unless You Ask It The Right Data Analysis Questions

datapine

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. They form the bedrock for the rest of this process.

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What is BCBS 239 Compliance?

Octopai

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.