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Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing

Astera

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. It applies selected business rules, calculations, data cleansing and data quality functions to the data.

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Data Vault 2.0: What You Need to Know

Astera

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What is Data Vault 2.0? Data Vault 2.0

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

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

Astera

Data Mapping: Create a mapping between source and target data fields in Salesforce. Specify how data will be transformed and mapped during the migration process. Ensure alignment with Salesforce data models and consider any necessary data cleansing or enrichment. What about the rows with missing data?

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Data Management 20/20: The Unacceptable Cost of Bad Data – Part 1

The Data Administration Newsletter

“…quite simply, the better and more accessible the data is, the better the decisions you will make.” – “When Bad Data Happens to Good Companies,” (environmentalleader.com) The Business Impact of an organization’s Bad Data can cost up to 25% of the company’s Revenue (Ovum Research) Bad Data Costs the US healthcare $314 Billion. (IT

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Analyst, Scientist, or Specialist? Choosing Your Data Job Title

Sisense

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another.

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Data Governance Framework: What is it? Importance, Pillars and Best Practices

Astera

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.