Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

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Pickl AI

JULY 25, 2024

In this blog, we’ll delve into the intricacies of data ingestion, exploring its challenges, best practices, and the tools that can help you harness the full potential of your data. Batch Processing In this method, data is collected over a period and then processed in groups or batches.

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Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

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Pickl AI

SEPTEMBER 18, 2024

The architecture is divided into two main categories: data at rest and data in motion. Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra. These systems handle the storage costs associated with keeping vast amounts of content and user data.

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Pickl AI

DECEMBER 9, 2024

What is Apache Hive? Hive is a data warehouse tool built on Hadoop that enables SQL-like querying to analyse large datasets. What is the Difference Between Structured and Unstructured Data? Batch processing handles large datasets collected over time, while real-time processing analyses data as it is generated.

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Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

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Pickl AI

JULY 29, 2024

Limited Support for Real-Time Processing While Hadoop excels at batch processing, it is not inherently designed for real-time data processing. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

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