Remove Data Integration Remove Enterprise Remove Forecasting Remove Prescriptive Analytics
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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics has become increasingly important in the enterprise as a means for analyzing and shaping business processes and improving decision-making and business results.

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

Smart Data Collective

The current BI trends show that in the future, the BI software will be more accessible, so that even non-techie workers will rely on data insights in their working routine. Prescriptive Analytics. The future of BI will also mean more integrations and collaboration. Automation & Augmented Analytics. QlickSense.

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Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

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Trending Technologies for BI & Financial Planning and AnalysisMaking AI Real (Part 2)

Jedox

We also took a first look at how fp&a and business intelligence professionals can start to derive tangible value from these technologies for Enterprise Performance Management. Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive.

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10 Best Big Data Analytics Tools You Need To Know in 2023

FineReport

With the right Big Data Tools and techniques, organizations can leverage Big Data to gain valuable insights that can inform business decisions and drive growth. What is Big Data? What is Big Data? Other sectors such as banking, healthcare, and education also take advantage of big data.

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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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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.