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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. One study forecasts that the market will be worth $23.8 While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. Both data warehouses and data lakes are used when storing big data.

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Optimizing the Energy Sector with Data Analytics

Cloudera

Effective use of data can have a direct impact on the cash flow of wind and solar generation companies in areas such as real-time decision making. With the right insights, energy production from renewable assets can be optimized and better predict the future of supply and demand. Towards a better customer experience.

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Swiss energy services company uses machine learning to see the future

CIO Business Intelligence

While scoping and modeling the project, IWB relied on support from SAP’s Global Center of Excellence and Customer Advisory, providing both business and application expertise to organizations engaged in SAP implementations and optimizing existing ones. Analytics would allow users to gain immediate insights into circumstances.

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How a data fabric overcomes data sprawls to reduce time to insights

IBM Big Data Hub

To truly understand the data fabric’s value, let’s look at a retail supply chain use case where a data scientist wants to predict product back orders so that they can maintain optimal inventory levels and prevent customer churn. How does a data fabric impact the bottom line?

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PODCAST: Unlocking the Value of AI in Supply Chain

bridgei2i

The 80s saw workflows being operationalized, and by the 90s, the advent of planning systems and demand forecasting systems had caused many advancements. The 2000s saw data warehouses being created and used as business intelligence picked up.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

IBM and AWS partnership focuses on delivering solutions in areas like: Supply chain optimization with AI-infused Planning Analytics IBM Planning Analytics on AWS offers a powerful platform for supply chain optimization, blending IBM’s analytics expertise with AWS’s cloud capabilities.