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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

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New Software Development Initiatives Lead To Second Stage Of Big Data

Smart Data Collective

The big data market is expected to be worth $189 billion by the end of this year. A number of factors are driving growth in big data. Demand for big data is part of the reason for the growth, but the fact that big data technology is evolving is another. Unstructured. Structured.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 115
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Get Ready For These Six 2020 Business Intelligence Trends

Smart Data Collective

New Avenues of Data Discovery. New data-collection technologies , like internet of things (IoT) devices, are providing businesses with vast banks of minute-to-minute data unlike anything collected before. AI-Powered Big Data Technology. Predictive Business Analytics. The Growing BI Analyst Shortage.

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Understanding Social And Collaborative Business Intelligence

datapine

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Interesting Read: THE DIFFERENT STAGES IN DATA ANALYTICS, AND WHERE DO YOU FIT IT IN AI AND ML ACTIVITIES? EXPERT OPINION]. Author Bio: . Website Link: [link] .

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 300
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7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. Azure Data Explorer. Bonus: Azure Stream Analytics and Azure Time Series Insights.

Data Lake 116