Remove Big Data Remove Forecasting Remove Prescriptive Analytics
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Big Data Skill sets that Software Developers will Need in 2020

Smart Data Collective

From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. Big Data Skillsets. Gartner estimates a retail IT spend forecast of $210.9 billion for IT services.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

Focus on the technologies and engineering components: e.g., sensors, monitoring, cloud-to-edge, microservices, serverless, insights-as-a-service APIs, IFTTT (IF-This-Then-That) architectures.

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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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What is the Future of Business Intelligence in the Coming Year?

Smart Data Collective

Business intelligence software will be more geared towards working with Big Data. Data Governance. One issue that many people don’t understand is data governance. It is evident that challenges of data handling will be present in the future too. Prescriptive Analytics.

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Optimizing Business Performance with Dynamics 365 and BI Dashboards: The Missing Link Between Data and Decisions

BizAcuity

Forecast trends and act strategically : Integration with advanced analytics and AI-powered insights helps businesses not only predict trends but also take proactive steps to stay ahead of competitors. Finance benefiting from automated forecasting, which reduces errors and ensures more accurate financial predictions.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Those who work in the field of data science are known as data scientists. To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark.