Remove Business Intelligence Remove Data Integration Remove Data Quality Remove Statistics
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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain.

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IBM named a leader in the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions

IBM Big Data Hub

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

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DataOps with Matillion and DataKitchen

DataKitchen

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataKitchen makes it simple to reuse and adapt existing code to implement the monitoring of data pipelines.

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How AWS helped Altron Group accelerate their vision for optimized customer engagement

AWS Big Data

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

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Data Observability and Monitoring with DataOps

DataKitchen

Figure 1: The process of transforming raw data into actionable business intelligence is a manufacturing process. When something goes wrong, you need to know about it as it’s happening to ensure that errors don’t reach customers or business partners. It’s not about data quality . Data Quality.

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What is a Data Pipeline?

Jet Global

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. The CEO also makes decisions based on performance and growth statistics. Data Quality.

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