Pickl AI

JULY 8, 2024

This blog explains how to build data pipelines and provides clear steps and best practices. From data collection to final delivery, we explore how these pipelines streamline processes, enhance decision-making capabilities, and ensure data integrity. What are Data Pipelines?

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Pickl AI

JANUARY 22, 2025

Introduction In today’s data-driven world, organizations generate approximately 2.5 quintillion bytes of data daily, highlighting the critical need for efficient data management. Database Management Systems (DBMS) serve as the backbone of data handling.

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Pickl AI

AUGUST 9, 2024

When data is organised hierarchically, queries can be optimised to aggregate data at various levels, improving performance and reducing processing time. Consistency in Reporting Hierarchies ensure that data is consistently structured across reports. organisational structures, product categories).

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Pickl AI

JANUARY 27, 2025

This distributed structure lowers hardware expenses and enables parallel processing of data-intensive tasks, making HDFS a foundation for handling vast volumes of information. Definition of HDFS HDFS is an open-source file system that manages files across a cluster of commodity servers.

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Pickl AI

AUGUST 11, 2024

Consider factors such as data volume, query patterns, and hardware constraints. Document and Communicate Maintain thorough documentation of fact table designs, including definitions, calculations, and relationships. Use slowly changing dimension (SCD) techniques to capture historical changes and maintain data integrity.

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Bugra Akyildiz

JUNE 29, 2024

A data janitor is a person who works to take big data and condense it into useful amounts of information. Also known as a "data wrangler", a data janitor sifts through data for companies in the information technology industry. Python, R), or specialized ETL (Extract, Transform, Load) tools.

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Bugra Akyildiz

NOVEMBER 20, 2022

We created zpy to make synthetic data easy, by simplifying the simulation (sim) creation process and providing an easy way to generate synthetic data at scale. The library is centered on the following concetps: ETL : central framework to create data pipelines. Zpy is available in GitHub. Do you have legacy notebooks?

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Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

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Pickl AI

DECEMBER 25, 2024

Here are some effective strategies to break down data silos: Data Integration Solutions Employing tools for data integration such as Extract, Transform, Load (ETL) processes can help consolidate data from various sources into a single repository.

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