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How to Shift from Data Science to Data Engineering

ODSC - Open Data Science

These professionals will work with their colleagues to ensure that data is accessible, with proper access. So let’s go through each step one by one, and help you build a roadmap toward becoming a data engineer. Identify your existing data science strengths. Stay on top of data engineering trends. Get more training!

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A beginner tale of Data Science

Becoming Human

Data Science You heard this term most of the time all over the internet, as well this is the most concerning topic for newbies who want to enter the world of data but don’t know the actual meaning of it. I’m not saying those are incorrect or wrong even though every article has its mindset behind the term ‘ Data Science ’.

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Introduction to Power BI Datamarts

ODSC - Open Data Science

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

Data Warehouses and Relational Databases It is essential to distinguish data lakes from data warehouses and relational databases, as each serves different purposes and has distinct characteristics. Schema Enforcement: Data warehouses use a “schema-on-write” approach. You can connect with her on Linkedin.

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Data architecture strategy for data quality

IBM Journey to AI blog

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.