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Data Integrity: The Foundation for Trustworthy AI/ML Outcomes and Confident Business Decisions

ODSC - Open Data Science

As critical data flows across an organization from various business applications, data silos become a big issue. The data silos, missing data, and errors make data management tedious and time-consuming, and they’re barriers to ensuring the accuracy and consistency of your data before it is usable by AI/ML.

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A Detailed Introduction on Data Lakes and Delta Lakes

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale.

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Customers and Banks Priorities Collide as AI Jolts Financial Industry

Smart Data Collective

The ability to connect data silos throughout the organization has been a Business Intelligence challenge for years, especially in banks where mergers and acquisitions have generated numerous and costly data silos. This integration is even more important, but much more complex with Big Data.

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How is the ‘Mesh’ Resolving Bottlenecks of Data Management

Smart Data Collective

It gained acceptance more than a decade ago when the industry was waking up to the potential urgency of big data that we are witnessing today. The Hadoop library enabled distributed processing across all points of data storage. Equally effective is the virtualization of data that integrates data silos using a logical layer.

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8 Data Lake Vendors to Make Your Data Life Easier in 2023

ODSC - Open Data Science

Oracle What Oracle offers is a big data service that is a fully managed, automated cloud service that provides enterprise organizations with a cost-effective Hadoop environment. Snowflake Snowflake is a cross-cloud platform that looks to break down data silos.

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Data platform trinity: Competitive or complementary?

IBM Journey to AI blog

A data fabric can consist of multiple data warehouses, data lakes, IoT/Edge devices and transactional databases. It can include technologies that range from Oracle, Teradata and Apache Hadoop to Snowflake on Azure, RedShift on AWS or MS SQL in the on-premises data center, to name just a few.

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

This centralization streamlines data access, facilitating more efficient analysis and reducing the challenges associated with siloed information. With all data in one place, businesses can break down data silos and gain holistic insights.