Remove Data Lake Remove Forecasting Remove Metadata
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Bridging the gap between mainframe data and hybrid cloud environments

CIO Business Intelligence

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Mainframes hold an enormous amount of critical and sensitive business data including transactional information, healthcare records, customer data, and inventory metrics.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

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Achieve your AI goals with an open data lakehouse approach

IBM Big Data Hub

With an open data lakehouse architecture approach, your teams can maximize value from their data to successfully adopt AI and enable better, faster insights. Why does AI need an open data lakehouse architecture? from 2022 to 2026. New insights and relationships are found in this combination. All of this supports the use of AI.

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6 BI challenges IT teams must address

CIO Business Intelligence

Jim Hare, distinguished VP and analyst at Gartner, says that some people think they need to take all the data siloed in systems in various business units and dump it into a data lake. But what they really need to do is fundamentally rethink how data is managed and accessed,” he says.

IT 131
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The Very Group adopts a data catalog to better organize and leverage its online retail capabilities

CIO Business Intelligence

One of the early projects on which he was able to add value through a partnership between his data hub and one of the business unit spokes was in building a new demand forecasting tool. Very has come full circle as a business built on catalog data, but it took some introspection in order to figure out the best way to get there.

IT 98
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Manage your data warehouse cost allocations with Amazon Redshift Serverless tagging

AWS Big Data

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.