Remove Data Integration Remove Data Processing Remove Predictive Analytics Remove Visualization
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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

Descriptive Analytics is used to determine “what happened and why.” ” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Having visually appealing graphics can also increase user adoption. Enables Predictive Analytics on data.

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Dresner’s Point: Ready for the “2014ization” of Business Intelligence?

Howard Dresner

Examples: user empowerment and the speed of getting answers (not just reports) • There is a growing interest in data that tells stories; keep up with advances in storyboarding to package visual analytics that might fill some gaps in communication and collaboration • Monitor rumblings about trend to shift data to secure storage outside the U.S.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

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How to choose the best AI platform

IBM Big Data Hub

Visual modeling: Combine visual data science with open source libraries and notebook-based interfaces on a unified data and AI studio. Will it be implemented on-premises or hosted using a cloud platform? Store operating platform : Scalable and secure foundation supports AI at the edge and data integration.

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What Is Embedded Analytics?

Jet Global

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Bottom line is that analytics has migrated from a trendy feature to a got-to-have. Their dashboards were visually stunning.