Knowledge Hut

JANUARY 2, 2024

By the time the course ends, you will have a vast project portfolio that can help you find excellent job roles at companies dedicated to improving business through cloud technology. Their top coding bootcamps program helps students build a well-rounded portfolio and gain expertise in various software technologies.

Coding 52

Coding Software Engineer Software Engineering Certification 52

Knowledge Hut

SEPTEMBER 6, 2023

Programming Languages : Good command on programming languages like Python, Java, or Scala is important as it enables you to handle data and derive insights from it. Data Analysis : Strong data analysis skills will help you define ways and strategies to transform data and extract useful insights from the data set.

Big Data 52

Big Data Certification Hadoop Scala 52

Knowledge Hut

JANUARY 22, 2024

Key topics include data collection, storage formats like databases, data warehouses, data lakes, transforming and processing data using ETL, batch and stream processing. Students work with SQL, NoSQL databases, Hadoop ecosystem, Spark, Kafka etc.

Data Science 52

Data Science Certification Education Data Lake 52

ProjectPro

APRIL 19, 2021

A data analyst collates all the data in one place and works with developers to create an ETL pipeline for the same by setting up business rules to transform the data on it should look once it is loaded into the system. Whatever learning path you choose, make sure you build a strong data analytics portfolio.

Portfolio 40

Portfolio Data Finance Certification 40

ProjectPro

JANUARY 19, 2022

Along with this, you will learn how to perform data analysis using GraphX and Neo4j. Apache Zeppelin Demo Big Data Project for Data Analysis : This project is best for beginners exploring big data tools. Depending on the company you want to work with, you will be asked to learn them deeply.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

NOVEMBER 10, 2016

The most in-demand job opportunities for professionals in the big data market are Hadoop developers, Hadoop admins,experts in Python and NoSQL. 5) 28% of Hadoopers possess NoSQL database skills. The kind of big data stored in Hadoop does not have a pre-defined schema or rather has a dynamic schema.

Hadoop 52

Hadoop NoSQL Java Electronics 52

ProjectPro

JULY 28, 2021

What does a data scientist at Google do? Google is a market leader in the tech space and you will get to develop and apply your skills in data analysis , data handling, and management as a Data Scientist. Why do you think NoSQL databases can be better than SQL databases?

Recruitment 40

Recruitment Data Science Machine Learning NoSQL 40

ProjectPro

APRIL 20, 2017

But when you browse through hadoop developer job postings, you become a little worried as most of the big data hadoop job descriptions require some kind of experience working on projects related to Hadoop. Hadoop projects for beginners are simply the best thing to do to learn the implementation of big data technologies like Hadoop.

Hadoop 40

Hadoop Big Data Coding Project 40

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). Beyond his work at Google, Deepanshu also mentors others on career and interview advice at topmate.io/deepanshu.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

ProjectPro

APRIL 8, 2015

AWS EMR is the best choice for organizations who do not want to manage thousands of servers directly - as they can rent out this cloud ready infrastructure of Amazon for big data analysis. Redshift is a completely managed petabyte scale data analytics solution that is cost effective in big data analysis with BI tools.

Hadoop 40

Hadoop Big Data Data Solutions Amazon Web Services 40

ProjectPro

JUNE 2, 2015

It is difficult to make sense out of billions of unstructured data points (in the form of news articles, forum comments, and social media data) without powerful technologies like Hadoop, Spark and NoSQL in place. Build an Awesome Job Winning Project Portfolio with Solved End-to-End Big Data Projects PREVIOUS NEXT <

Big Data 40

Big Data Hadoop Banking Retail 40

ProjectPro

MAY 23, 2015

The main objective of migrating the Hadoop clusters was to combine 10 different websites into a single website so that all the unstructured data generated is collected into a new Hadoop cluster. Walmart acquired a small startup Inkiru based in Palo Alto, California to boost its big data capabilites.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

OCTOBER 15, 2014

Hive Depending on your purpose and type of data you can either choose to use Hive Hadoop component or Pig Hadoop Component based on the below differences : 1) Hive Hadoop Component is used mainly by data analysts whereas Pig Hadoop Component is generally used by Researchers and Programmers. 11) Pig supports Avro whereas Hive does not.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Keep Learning: Stay acquainted with the latest technologies and trends.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Knowledge Hut

JANUARY 23, 2024

Python: Python is a type of programming language that is mainly used in the development of websites and apps, automation, and data analysis. SQL: In a relational data management system, data extraction and structuring are done using the programming language SQL. NPM: The package manager specifically made for Node.js

MongoDB 98

MongoDB Programming Language Java MySQL 98

AltexSoft

MAY 14, 2021

Any irrelevant or flawed data needs to be removed or taken into account. Several data quality tools can detect any flaws in datasets and conduct cleansing activities on them. Data analysis. To make sense of the huge amounts of data, there are several techniques and practices. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

NOVEMBER 7, 2023

Applications of Cloud Computing in Big Data Analysis Companies can acquire new insights and optimize business processes by harnessing the computing power of cloud computing. Every day, enormous amounts of data are collected from business endpoints, cloud apps, and the people who engage with them.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

ProjectPro

JANUARY 24, 2023

It will also cover a step-by-step Google BigQuery tutorial to help you get started with your data warehousing solutions. Google BigQuery Data Analysis Workflows Google BigQuery Architecture- A Detailed Overview Google BigQuery Datatypes BigQuery Tutorial for Beginners: How To Use BigQuery? Q: Is BigQuery SQL or NoSQL?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

AUGUST 11, 2021

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

SEPTEMBER 26, 2021

Build an Awesome Job Winning Data Engineering Projects Portfoli o Technical Skills Required to Become a Big Data Engineer Database Systems: Data is the primary asset handled, processed, and managed by a Big Data Engineer. You must have good knowledge of the SQL and NoSQL database systems.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 17, 2015

A big-data resume with Hadoop skills highlighted on the list will attract employer’s attention immediately. 2) NoSQL Databases -Average Salary$118,587 If on one side of the big data virtuous cycle is Hadoop, then the other is occupied by NoSQL databases. from the previous year.

Cloud Computing 40

Cloud Computing Big Data R (Programming) Big Data Skills 40

AltexSoft

JUNE 7, 2021

Data storage options. Apache HBase , a noSQL database on top of HDFS, is designed to store huge tables, with millions of columns and billions of rows. Its in-memory processing engine allows for quick, real-time access to data stored in HDFS. Alternatively, you can opt for Apache Cassandra — one more noSQL database in the family.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 31, 2023

This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files. Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

MARCH 23, 2016

Since then, it is evolving continuously and changing the big data world. It has been 10 years since Hadoop first disrupted the Big Data world, but many are still unaware of how much this technology has changed the data analysis scene. Check Out Apache Hive Real Time Projects to Build Your Portfolio How to use Hadoop?

Hadoop 40

Hadoop IT Big Data Retail 40

ProjectPro

NOVEMBER 15, 2021

Contributing to an open-source big data project has numerous potential benefits for developers and data scientists, including acquiring new skills, interacting with the community, developing a solid network, and sharpening skillset. It has the potential to query large datasets from numerous heterogeneous data sources.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

AUGUST 31, 2018

Companies that seek rapid data analysis or graphics processing have two options: purchase additional hardware or migrate to the cloud. Azure and AWS both provide database services, regardless of whether you need a relational database or a NoSQL offering. The purpose of public cloud services is to achieve this.

AWS 45

AWS Cloud Amazon Web Services Cloud Computing 45

ProjectPro

AUGUST 26, 2015

. “We call this as the problem of BIG DATA” and hence the term “BIG DATA” was coined in this setting. 1998 -An open source relational database was developed by Carlo Strozzi who named it as NoSQL. 2011 - IBM’s supercomputer Watson analyses 200 million pages approximately 4TB of data in seconds.

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

MARCH 16, 2015

CASI pr the Complex Adaptive Systems Initiative at the Arizona State University is developing a genomic data lake with petabytes of genetic data on individuals, treatments, potentially helping in identifying the cancer gene and providing the base to develop life saving cancer treatments through big data analysis.

Healthcare 40

Healthcare Big Data Project Hospitality 40

ProjectPro

JUNE 23, 2016

The file format may be delimited text files, Sequence files where the record data is stored in a serialized format, or binary Avro files. Hence, Sqoop allows bidirectional data transfer between Hadoop and RDBMS with fast performance and optimal system resource utilization. Data can be directly loaded into Hive/HBase/HDFS.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 21, 2015

IBM has a nice, simple explanation for the four critical features of big data: a) Volume –Scale of data b) Velocity –Analysis of streaming data c) Variety – Different forms of data d) Veracity –Uncertainty of data Here is an explanatory video on the four V’s of Big Data 3.

Hadoop 40

Hadoop Big Data Metadata Java 40

Knowledge Hut

DECEMBER 13, 2023

Tiger Analytics Tiger Analytics is among the important big data analytics companies. Tiger Analytics is a global leader in data analytics, and they provide organizations with a variety of data analysis options. HP Enterprise HP Enterprise is one of the biggest names among big data tech companies.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

ProjectPro

JUNE 4, 2015

The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis. Big data applications using Apache Hadoop continue to run even if any of the individual cluster or server fails owing to the robust and stable nature of Hadoop.

Hadoop 52

Hadoop Architecture IT Java 52