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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Experience the power of Business Intelligence with our 14-days free trial! Why Is Business Intelligence So Important?

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

These issues dont just hinder next-gen analytics and AI; they erode trust, delay transformation and diminish business value. Its a strategic imperative that demands the focus of both technology and business leaders. Data fabric Metadata-rich integration layer across distributed systems. federal agencies.

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Top 10 Metadata Management Influencers, Sites, and Blogs You Must Follow in 2021

Octopai

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story. Donna Burbank. Forbes Technology Council.

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What is Metadata Management?

Octopai

Modern data processing depends on metadata management to power enhanced business intelligence. Metadata is of course the information about the data, and the process of managing it is mysterious to those not trained in advanced BI. In this article, you will learn: What does metadata management do?

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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. We will go over them in the third part of this article. 2 – Data profiling. 3 – Defining data quality.

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Metadata-Driven Data Warehouses are Ideal

TDAN

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Here are some typical ways organizations begin using machine learning: Build upon existing analytics use cases: e.g., one can use existing data sources for business intelligence and analytics, and use them in an ML application. Metadata and artifacts needed for audits. Use ML to unlock new data types—e.g., images, audio, video.