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What is big data and why is it important to BusinessĀ ?

Analysts Corner

Velocity refers to the speed at which data is generated, analyzed, and processed. Variety refers to the different types of data generated, such as text, images, and video. Why is big data important to business? Healthcare providers can use big data to analyse patient data to improve treatment outcomes and reduce costs.

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How AI is Changing the Data Integration ProcessĀ 

Astera

It utilizes advanced data-matching algorithms that identify matching data elements across different data sources and automatically map s them to the correct location in the target system. These algorithms are particularly useful when dealing with data sources that have different data formats or structures.

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What is Data Preprocessing? Definition, Importance, and Steps

Astera

Data profiling involves examining the data using summary statistics and distributions to understand its structure, content, and quality. Example: A retail manager analyzes a dataset of customer purchases to find average spending, most common items, and times of purchase to devise a data-driven marketing strategy.

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Fundamentals of Data Analytics

The BAWorld

The blog discusses key elements including tools, applications, future trends, and fundamentals of data analytics, providing comprehensive insights for professionals and enthusiasts in the field. A retailer, for example, can examine sales data, customer feedback, and marketing campaign data to determine why sales fell in a specific month.

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Snowflake ETL Tools: Top 7 Options to Consider in 2024

Astera

Snowflake has restructured the data warehousing scenario with its cloud-based architecture. Businesses can easily scale their data storage and processing capabilities with this innovative approach.

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Data Modeling: Techniques, Best Practices, & Why It Matters?

Astera

With a combination of text, symbols, and diagrams, data modeling offers visualization of how data is captured, stored, and utilized within a business. It serves as a strategic exercise in understanding and clarifying the business’s data requirements, providing a blueprint for managing data from collection to application.

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Data Warehouse vs. Database: Understanding the Differences

Astera

This process requires careful planning and implementation to ensure the integrated data is accurate, consistent, and reliable. Subject-Oriented: The subject-oriented nature of data warehouses allows organizations to focus on specific business areas.