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Using Data-Driven Lean Thinking to Optimize Business Processes

Smart Data Collective

Data-driven decision-making has become a major element of modern business. A growing number of businesses use big data technology to optimize efficiency. However, companies that have a formal data strategy are still in the minority. Lean Thinking and Big Data Can Be Merged for Superior Decision-Making.

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Data-Driven Marketing Strategies to Supercharge eCommerce Businesses

Smart Data Collective

Big data has become a highly invaluable aspect of modern business. More companies are using sophisticated data analytics and AI tools to overhaul their business models. Some industries have become more dependent on big data than others. The e-commerce sector has been one of the most affected by major advances in data technology.

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Why Data-Driven SEO is Crucial for SMEs in This Recession

Smart Data Collective

More small businesses are leveraging big data technology these days. One of the many reasons that they use big data is to improve their SEO. Data-driven SEO is going to be even more important as the economy continues to stagnate. This includes choosing the right pages to optimize.

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ANZ Bank’s Advances Data-Driven Analytics With Cloudera

Cloudera

Data and analytics are the essential engines in this strategy which entails upgrading the bank’s core banking technology to deliver reliable, efficient, and secure services for their customers while safeguarding critical data. The approach offered lower risks and allowed for comprehensive platform and application testing.

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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Data team morale is consistent with DataKitchen’s own research. We surveyed 600 data engineers , including 100 managers, to understand how they are faring and feeling about the work that they are doing.

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How generative AI will revolutionize supply chain 

IBM Big Data Hub

In the age of digital transformation, the integration of advanced technologies like generative artificial intelligence brings a new era of innovation and optimization. From demand forecasting to route optimization, inventory management and risk mitigation, the applications of generative AI are limitless.

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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. 10) Data Quality Solutions: Key Attributes.