Remove Business Intelligence Remove Data Governance Remove Unstructured Data
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Data Integrity for AI: What’s Old is New Again

Precisely

Data marts involved the creation of built-for-purpose analytic repositories meant to directly support more specific business users and reporting needs (e.g., But those end users werent always clear on which data they should use for which reports, as the data definitions were often unclear or conflicting.

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The Challenge of Data Quality and Availability—And Why It’s Holding Back AI and Analytics

Striim

But theyre only as good as the data they rely on. If the underlying data is incomplete, inconsistent, or delayed, even the most advanced AI models and business intelligence systems will produce unreliable insights. Ensuring data quality means fewer biases and better outcomes.

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How DataOS Nails Gartner’s Magic Quadrant for Data Integration

The Modern Data Company

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

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How DataOS Nails Gartner’s Magic Quadrant for Data Integration

The Modern Data Company

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

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Cloudera Open Data Lakehouse Named a Finalist in the CRN Tech Innovator Awards

Cloudera

This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics. The root of the problem comes down to trusted data.

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Data Engineering: A Formula 1-inspired Guide for Beginners

Towards Data Science

We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Lake A data lake would serve as a repository for raw and unstructured data generated from various sources within the Formula 1 ecosystem: telemetry data from the cars (e.g.

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Top 30 Data Scientist Skills to Master in 2024

Knowledge Hut

Statistics are used by data scientists to collect, assess, analyze, and derive conclusions from data, as well as to apply quantifiable mathematical models to relevant variables. Microsoft Excel An effective Excel spreadsheet will arrange unstructured data into a legible format, making it simpler to glean insights that can be used.

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