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Health Data Management | Challenges and Best Practices

Astera

Billion by 2026 , showing the crucial role of health data management in the industry. Source: Precedence Research The increased volumes of information, varying in type and velocity, present immense potential to derive value from this information and aid the digital transformation of the healthcare industry.

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Salesforce Data Migration: What Is It & How to Set It Up?

Astera

Ensure alignment with Salesforce data models and consider any necessary data cleansing or enrichment. Data Extraction: Extract data from the source systems according to the mapping plan. Data Transformation: Apply necessary transformations to the extracted data to align it with Salesforce requirements.

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Skills and Tools Every Data Engineer Needs to Tackle Big Data

Sisense

Data engineers also need to have in-depth database knowledge of SQL and NoSQL since one of the main requirements of the job will be to collect, store, and query information from these databases in real-time. In this course, you’ll learn how to manipulate data and build queries that communicate with more than one table.

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How to Build a Data Governance Strategy for Your Organization

Astera

It would focus on what the customer wants, how the market is behaving, and what other competitors are doing, all through the lens of fresh, accurate data. In short, a data governance strategy includes the following: Establishing principles, policies, and procedures for data management.

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12 Best Data Mapping Tools & Solutions in 2023

Astera

Managing data effectively is a multi-layered activity—you must carefully locate it, consolidate it, and clean it to make it usable. One of the first steps in the data management cycle is data mapping. Data mapping is the process of defining how data elements in one system or format correspond to those in another.

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5 Best Claims Automation Software in 2024

Astera

IBM estimates that the insurance industry contributes significantly to the creation of 2.5 quintillion bytes of data every day, with claims data being a major contributor to this massive volume. Manual processing of this data is no longer practical, given the large data volume.

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Understanding Data Warehousing Concepts for Business Analysts

Business Analysis Knowledge Share

This article aims to provide a comprehensive overview of Data Warehousing, breaking down key concepts that every Business Analyst should know. Introduction As businesses generate and accumulate vast amounts of data, the need for efficient data management and analysis becomes paramount.