Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. Which one is right for your business? What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications.

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Data Lakes Data Warehouse Hadoop Machine Learning 221

Data Science Dojo

JULY 6, 2023

Apache Hadoop: Apache Hadoop is an open-source framework for distributed storage and processing of large datasets. It provides a scalable and fault-tolerant ecosystem for big data processing. Looker: Looker is a business intelligence and data visualization platform.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Key Features : Cost Efficiency : Pay only for the resources you use.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

DECEMBER 2, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

As organisations grapple with this vast amount of information, understanding the main components of Big Data becomes essential for leveraging its potential effectively. Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52