Knowledge Hut

DECEMBER 26, 2023

Data Architects design, create and maintain database systems according to the business model requirements. In other words, they develop, maintain, and test Big Data solutions. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Knowledge Hut

JUNE 23, 2023

You should be able to work on complex projects and design and implement data solutions. The next stage is to work as a Senior Data Engineer – After you gain expertise in multiple programming languages, databases, and big data technologies, you should be able to work on complex data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

Knowledge Hut

DECEMBER 27, 2023

But ‘big data’ as a concept gained popularity in the early 2000s when Doug Laney, an industry analyst, articulated the definition of big data as the 3Vs. The Latest Big Data Statistics Reveal that the global big data analytics market is expected to earn $68 billion in revenue by 2025. Cons: Occupies huge RAM.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

Knowledge Hut

NOVEMBER 17, 2023

An Azure Data Engineer locates and resolves difficult data-related issues, enhances the performance and scalability of data solutions, and works cooperatively with other teams to develop solutions. The main duties of an Azure Data Engineer are planning, developing, deploying, and managing the data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Databand.ai

DECEMBER 13, 2022

Follow Charles on LinkedIn 3) Deepak Goyal Azure Instructor at Microsoft Deepak is a certified big data and Azure Cloud Solution Architect with more than 13 years of experience in the IT industry. He is also an AWS Certified Solutions Architect and AWS Certified Big Data expert.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Rockset

DECEMBER 9, 2021

Companies that undertook big data projects ran head-long into the high cost, rigidity and complexity of managing complex on-premises data stacks. Lifting-and-shifting their big data environment into the cloud only made things more complex. Change data capture (CDC) streams. The problem?

Transportation 52

Transportation BI SQL Database 52

ProjectPro

MAY 19, 2015

.” A researchreport by Markets and Markets Research anticipates that Hadoop and Big Data Analytics market will reach close to $13.9 This prediction is turning true as Hadoop is the technology being leveraged extensively to harness Big Data in 2015. billion from 2012 to 2017. ” “Hadoop is an emerging skill.

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

Knowledge Hut

SEPTEMBER 6, 2023

Data Mining and ETL : For gathering, transforming, and integrating data from diverse sources, proficiency in data mining techniques and Extract, Transform, Load (ETL) processes is required. These platforms provide out of the box big data tools and also help in managing deployments. You don’t need any degree or experience.

Big Data 52

Big Data Certification Hadoop Kafka 52

ProjectPro

NOVEMBER 10, 2016

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Educational Requirements for a Hadoop Developer Hadoop is a technology that needs to be mastered on its own. What are the blogs, books and courses you should take to become a Hadoop developer or administrator?

Hadoop 52

Hadoop NoSQL Java Big Data 52

ProjectPro

JANUARY 19, 2022

A data engineer should be aware of how the data landscape is changing. They should also be mindful of how data systems have evolved and benefited data professionals. Explore the distinctions between on-premises and cloud data solutions. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

JULY 30, 2021

Big data analytics - Big data and Cloud technologies go hand in hand and essentially make systems faster, scalable, failsafe, high-performance, and cheaper. Apache Spark forms the complete big data solution along with HDFS, Yarn, Map-Reduce. These instances use their local storage to store data.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40