U-Next

SEPTEMBER 29, 2022

According to the World Economic Forum’s Future of Jobs Report 2020 , these roles are the most in-demand across big data industries. There is an increased demand for data professionals. . Who Is a Data Analyst, and What Do They Do? . Who Is a Data Scientist, and What Do They Do? . Data Analytics .

Data Science 40

Data Science Data Analytics Data Mining Algorithm 40

Knowledge Hut

FEBRUARY 15, 2023

Data analysis starts with identifying prospectively benefiting data, collecting them, and analyzing their insights. Further, data analysts tend to transform this customer-driven data into forms that are insightful for business decision-making processes. Spotfire focuses more on data visualization.

Data Cleanse 52

Data Cleanse Entertainment Business Intelligence Recruitment 52

ProjectPro

JANUARY 31, 2023

With the introduction of advanced machine learning algorithms , underwriters are bringing in more data for better risk management and providing premium pricing targeted to the customer. This explains why the insurance sector is acquiring an increasing amount of data.

Insurance 75

Insurance Machine Learning Project Algorithm 75

Knowledge Hut

NOVEMBER 20, 2023

Nowadays, it's also used as a standalone product by many other companies that use it for their analytics needs. Splunk Splunk is a software company specializing in data analytics. They offer products that help organizations collect, search, analyze and visualize their machine data.

Amazon Web Services 52

Amazon Web Services Java AWS Cloud 52

ProjectPro

AUGUST 24, 2021

So, working on a data warehousing project that helps you understand the building blocks of a data warehouse is likely to bring you more clarity and enhance your productivity as a data engineer. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

U-Next

AUGUST 11, 2022

Data Science is an interdisciplinary field that blends programming skills, domain knowledge, reasoning skills, mathematical and statistical skills to generate value from a large pool of data. Skill requirements for Data Science. Knowing algorithms, mathematics, statistics, and machine learning are essential.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40