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Build a strong data foundation for AI-driven business growth

CIO Business Intelligence

In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. If the data volume is insufficient, it’s impossible to build robust ML algorithms. If the data quality is poor, the generated outcomes will be useless.

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Cloud analytics migration: how to exceed expectations

CIO Business Intelligence

A modern data and artificial intelligence (AI) platform running on scalable processors can handle diverse analytics workloads and speed data retrieval, delivering deeper insights to empower strategic decision-making. Business objectives must be articulated and matched with appropriate tools, methodologies, and processes.

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Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact

DataKitchen

A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. 73% of data practitioners do not trust their data (IDC). The challenge is not simply a technical one.

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How to Do Data Modeling the Right Way

erwin

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. Nine Steps to Data Modeling.

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Top 10 governance, risk, and compliance certifications

CIO Business Intelligence

The goal of GRC, in general, is to ensure that proper policies and controls are in place to reduce risk, to set up a system of checks and balances to alert personnel when new risks materialize, and to manage business processes more efficiently and proactively. Enter the need for competent governance, risk and compliance (GRC) professionals.

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Getting Started With People Analytics

Sisense

As companies digitally transform and become data-driven, each department and team needs to find its own ways to embrace data and insights to make smarter decisions. HR professionals are awash in hiring and employee data of all kinds. Again: Today, HR teams are inundated with HR data from a variety of sources.

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The Third Pillar of Data Culture: Data Governance

Alation

The same could be said about data governance : ask ten experts to define the term, and you’ll get eleven definitions and perhaps twelve frameworks. However it’s defined, data governance is among the hottest topics in data management. This is the final post in a four-part series discussing data culture.