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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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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

As we have already said, the challenge for companies is to extract value from data, and to do so it is necessary to have the best visualization tools. Over time, it is true that artificial intelligence and deep learning models will be help process these massive amounts of data (in fact, this is already being done in some fields).

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

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Capgemini and IBM Ecosystem strengthen partnership for Drone-as-a-Service

IBM Big Data Hub

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. billion by 2029, at a CAGR of 28.58% in the forecast period. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification.

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10 everyday machine learning use cases

IBM Big Data Hub

ML also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. Many stock market transactions use ML.