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Common Business Intelligence Challenges Facing Entrepreneurs

datapine

“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith. Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors. Let’s get started!

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Understanding Social And Collaborative Business Intelligence

datapine

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

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Why optimize your warehouse with a data lakehouse strategy

IBM Big Data Hub

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Deploy and Optimize Your Snowflake Environment Faster With Accelerators

CDW Research Hub

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

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Become More Data-Driven by Evolving Analytics Workloads

CIO Business Intelligence

Data-driven organizations understand that data, when analyzed, is a strategic asset. It forms the basis for making informed decisions around product innovation, dynamic pricing, market expansion, and supply chain optimization. Cloudera and Dell Technologies for More Data Insights. It’s the “new oil.”

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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.