Knowledge Hut

SEPTEMBER 6, 2023

Problem-Solving Abilities: Many certification courses provide projects and assessments which require hands-on practice of big data tools which enhances your problem solving capabilities. Networking Opportunities: While pursuing big data certification course you are likely to interact with trainers and other data professionals.

Big Data 52

Big Data Certification Hadoop Scala 52

Knowledge Hut

SEPTEMBER 25, 2023

Joining a credible Data Analyst Bootcamp training is an effective way to increase your knowledge. Languages : Prior to obtaining a related certificate, it's crucial to have at least a basic understanding of SQL since it is the most often used language in data analytics. Python is useful for various data analytics positions.

Certification 52

Certification Business Analyst Big Data Data Analysis 52

Databand.ai

DECEMBER 13, 2022

Deepanshu’s skills include SQL, data engineering, Apache Spark, ETL, pipelining, Python, and NoSQL, and he has worked on all three major cloud platforms (Google Cloud Platform, Azure, and AWS). He also shares thoughts and advice regularly on LinkedIn, centered around topics like SQL, data engineering, careers, and interviews.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

JULY 4, 2023

Data Engineer They do the job of finding trends and abnormalities in data sets. They create their own algorithms to modify data to gain more insightful knowledge. Programming languages like Python and SQL that deal with data structures are essential for this position. There is a demand for data analysts worldwide.

Data Analytics 52

Data Analytics Data Architect Transportation Data Science 52

ProjectPro

DECEMBER 7, 2021

AWS Glue You can easily extract and load your data for analytics using the fully managed extract, transform, and load (ETL) service AWS Glue. To organize your data pipelines and workflows, build data lakes or data warehouses, and enable output streams, AWS Glue uses other big data tools and AWS services.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. Hadoop is highly scalable.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

APRIL 20, 2017

The collection of these projects on Hadoop and Spark will help professionals master the big data and Hadoop ecosystem concepts learnt during their hadoop training. Hive supports an SQL-like interface for retrieving data from several databases and file systems that blend with Hadoop. Implementing a Big Data project on AWS.

Hadoop 40

Hadoop Big Data Coding Project 40

ProjectPro

NOVEMBER 30, 2021

Explore SQL Database Projects to Add them to Your Data Engineer Resume. A senior business analyst is often expected to possess knowledge of Big Data tools. Thus, you will find the projects described below rely on these tools. So, please refer to the source code links for help.

Business Analyst 52

Business Analyst Project Retail Datasets 52

ProjectPro

NOVEMBER 14, 2015

Hadoop ecosystem has a very desirable ability to blend with popular programming and scripting platforms such as SQL, Java , Python, and the like which makes migration projects easier to execute. From Data Engineering Fundamentals to full hands-on example projects , check out data engineering projects by ProjectPro 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

AUGUST 21, 2015

Unorganized and raw data that cannot be categorized as semi-structured or structured data is referred to as unstructured data. are all examples of unstructured data. This data needs to be stored in HDFS. Sqoop provides the capability to store large sized data into a single field based on the type of data.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

JUNE 26, 2023

Such tables create the basis for business intelligence, traditional data analytics, and time series forecasting (if data about the same item is collected at different points of time.) Structured data is modeled to be easily searchable and occupy minimal storage space. No wonder only 0.5 and its value (male, red, $100, etc.).

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52