Data Science Dojo

JANUARY 12, 2023

Analytics Data lakes give various positions in your company, such as data scientists, data developers, and business analysts, access to data using the analytical tools and frameworks of their choice. You can perform analytics with Data Lakes without moving your data to a different analytics system. 4.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Pickl AI

JULY 18, 2023

While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases. SQL’s powerful functionalities help in extracting and transforming data from various sources, thus helping in accurate data analysis.

Data Science 52

Data Science SQL Data Scientist Python 52

Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. It is known for its high fault tolerance and scalability.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

AUGUST 1, 2023

Data Pipeline Orchestration: Managing the end-to-end data flow from data sources to the destination systems, often using tools like Apache Airflow, Apache NiFi, or other workflow management systems. It teaches Pandas, a crucial library for data preprocessing and transformation.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. It is known for its high fault tolerance and scalability.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JULY 29, 2024

Some key applications of Hadoop clusters in big data include: Data Warehousing Hadoop clusters can be used as cost-effective data warehousing solutions , storing and processing large volumes of data for business intelligence and reporting purposes. Apache Hadoop, Cloudera, Hortonworks).

Hadoop 52

Hadoop Clustering Big Data Big Data 52

Pickl AI

SEPTEMBER 11, 2024

This layer includes tools and frameworks for data processing, such as Apache Hadoop, Apache Spark, and data integration tools. Data as a Service (DaaS) DaaS allows organisations to access and integrate data from various sources without the need for complex data management.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52