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How Data Cleansing Can Make or Break Your Business Analytics

Smart Data Collective

A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. The Global BPO Business Analytics Market was worth nearly $17 billion last year. One of the biggest issues pertains to data quality.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Businesses of all sizes are no longer asking if they need increased access to business intelligence analytics but what is the best BI solution for their specific business. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. These issues dont just hinder next-gen analytics and AI; they erode trust, delay transformation and diminish business value.

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Data trust and the evolution of enterprise analytics in the age of AI

CIO Business Intelligence

For many, the level of sophistication can easily range from more sophisticated solutions like Power BI, Tableau, SAP Analytics or IBM Cognos to mid-tier solutions like Domo, Qlik or the tried and true elder statesman for all business analytics consumers, Excel.

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Top 5 Tips For Conducting Successful BI Projects With Examples & Templates

datapine

Maximum security and data privacy. Facing the challenges of poor data quality, dispersed through a number of spreadsheets and databases, this financial company was unable to track financial data in real-time and generate valuable insights needed to ensure their vendor payment, managed by the accounts payable department, is accurate and fast.

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

The field of data observability has experienced substantial growth recently, offering numerous commercial tools on the market or the option to build a DIY solution using open-source components. The introduction of generative AI (genAI) and the rise of natural language data analytics will exacerbate this problem.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

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