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A Beginner’s Guide to Data Warehousing

Unite.AI

In this digital economy, data is paramount. Today, all sectors, from private enterprises to public entities, use big data to make critical business decisions. However, the data ecosystem faces numerous challenges regarding large data volume, variety, and velocity. Enter data warehousing!

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10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data. Data Integration: Combining data from multiple sources to create a unified view for analysis and decision-making.

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The Data Dilemma: Exploring the Key Differences Between Data Science and Data Engineering

Pickl AI

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

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Smart Retail: Harnessing Machine Learning for Retail Demand Forecasting Excellence

Pickl AI

Unlike supervised learning, where the algorithm is trained on labeled data, unsupervised learning allows algorithms to autonomously identify hidden structures and relationships within data. These algorithms can identify natural clusters or associations within the data, providing valuable insights for demand forecasting.

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The Age of Health Informatics: Part 1

Heartbeat

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

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What is Hadoop and How Does It Work?

Pickl AI

Hadoop has become a highly familiar term because of the advent of big data in the digital world and establishing its position successfully. The technological development through Big Data has been able to change the approach of data analysis vehemently. Let’s find out from the blog! What is Hadoop?

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. How would you segment customers based on their purchasing behaviour?