Cloud Computing Data Management Data Modelling 
Whizlabs
APRIL 19, 2021
It is loud and clear that Cloud Computing is fundamental to the new wave of digital transformation. In the year of 2020, with everyone working from home, better cloud storage and computing strategies have helped many organizations to grow higher while some were struggling to adapt to the changes.
Astera
FEBRUARY 27, 2024
These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.
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Astera
FEBRUARY 27, 2024
These systems can be part of the company’s internal workings or external players, each with its own unique data models and formats. ETL (Extract, Transform, Load) process : The ETL process extracts data from source systems to transform it into a standardized and consistent format, and then delivers it to the data warehouse.
Astera
FEBRUARY 28, 2024
In other words, a data warehouse is organized around specific topics or domains, such as customers, products, or sales; it integrates data from different sources and formats, and tracks changes in data over time. Techniques like capacity planning, modular design, and embracing cloud computing are your go-to strategies.
Astera
NOVEMBER 30, 2023
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
Astera
APRIL 27, 2023
Data lakes provide businesses with a flexible and cost-effective way to store structured or semi-structured data of any type at any volume. On the other hand, data warehouses are better for the organized archiving of structured data for analysis purposes. What is a Data Lake?
Marutitech
JANUARY 21, 2022
The primary responsibility of a data science manager is to ensure that the team demonstrates the impact of their actions and that the entire team is working towards the same goals defined by the requirements of the stakeholders. 2. Manage people. Interpreting data. Data science is the sexiest job of the 21st century.
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