ProjectPro

MARCH 15, 2016

Hadoop is beginning to live up to its promise of being the backbone technology for Big Data storage and analytics. Companies across the globe have started to migrate their data into Hadoop to join the stalwarts who already adopted Hadoop a while ago. All Data is not Big Data and might not require a Hadoop solution.

Hadoop 40

Hadoop Retail Healthcare Banking 40

Knowledge Hut

SEPTEMBER 6, 2023

Data Science Bootcamp course from KnowledgeHut will help you gain knowledge on different data engineering concepts. It will cover topics like Data Warehousing,Linux, Python, SQL, Hadoop, MongoDB, Big Data Processing, Big Data Security,AWS and more.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

ProjectPro

SEPTEMBER 26, 2021

As a Big Data Engineer, you shall also know and understand the Big Data architecture and Big Data tools. Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. You will get to learn about data storage and management with lessons on Big Data tools.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 18, 2024

Host: It is hosted by Google and challenges participants to solve a set of data science problems. Eligibility : Data science competition Kaggle is for everything from cooking to data mining. Eligibility : If you're interested in participating in the Driven Data Science Competition, you'll first need to register.

Data Science 98

Data Science Recruitment Big Data Machine Learning 98

ProjectPro

JUNE 24, 2021

Table of Contents Skills Required for Data Analytics Jobs Why Should Students Work on Big Data Analytics Projects ? Some amount of experience working on Python projects can be very helpful to build up data analytics skills. Testing is a very complex process which costs a company a fair amount of time, energy and money.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

Knowledge Hut

DECEMBER 26, 2023

This big data book for beginners covers the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

AltexSoft

MAY 12, 2023

It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. Analysis of structured data is typically performed using SQL queries and data mining techniques. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

SEPTEMBER 23, 2022

Traditional data processing technologies have presented numerous obstacles in analyzing and researching such massive amounts of data. To address these issues, Big Data technologies such as Hadoop were established. These Big Data tools aided in the realization of Big Data applications. . Education Sector .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

MARCH 14, 2014

Every department of an organization including marketing, finance and HR are now getting direct access to their own data. This is creating a huge job opportunity and there is an urgent requirement for the professionals to master Big Data Hadoop skills. In 2015, big data has evolved beyond the hype.

Hadoop 40

Hadoop Big Data Data Mining Retail 40

Knowledge Hut

MARCH 7, 2024

Importance of Big Data Analytics Tools Using Big Data Analytics has a lot of benefits. Big data analytics tools and technology provide high performance in predictive analytics, data mining, text mining, forecasting data, and optimization. What are the 4 different kinds of Big Data analytics?

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52