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

Astera

Only 5% of businesses feel they have data management under control, while 77% of industry leaders consider growing volume of data one of the biggest challenges. It applies selected business rules, calculations, data cleansing and data quality functions to the data.

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Testing and Monitoring Data Pipelines: Part Two

Dataversity

In part one of this article, we discussed how data testing can specifically test a data object (e.g., table, column, metadata) at one particular point in the data pipeline.

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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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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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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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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.