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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of data, analytics, and machine learning. Data Platforms. Temporal data and time-series.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

With the right Big Data Tools and techniques, organizations can leverage Big Data to gain valuable insights that can inform business decisions and drive growth. What is Big Data? What is Big Data? It is an ever-expanding collection of diverse and complex data that is growing exponentially.

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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

As data volumes continue to increase alongside a correlating number of business requests, modern insurance data leaders face a nuanced set of challenges. Accelerated demand in AI-enabled innovations has recently compounded these issues, prioritizing the need for new capabilities that require even more robust data foundations.

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DataOps Enables Your Data Fabric

DataKitchen

Industry analysts who follow the data and analytics industry tell DataKitchen that they are receiving inquiries about “data fabrics” from enterprise clients on a near-daily basis. Gartner included data fabrics in their top ten trends for data and analytics in 2019.

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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. Adding DataOps to ETL processes is the secret to eliminating errors and dramatically improving analytic cycle times.

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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Overlooking these data resources is a big mistake.