ProjectPro

MAY 23, 2015

Table of Contents How Walmart uses Big Data? 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. Big data solutions at Walmart are developed with the intent of redesigning global websites.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

JUNE 6, 2025

AWS offers the best serverless cloud data analytics solutions, including solutions for data warehousing, big data solutions, data integration, and much more. Table of Contents Why Learn AWS for Data Engineering? What is Data Engineering?? What is AWS for Data Engineering?

AWS 40

AWS Data Engineer Data Engineering Engineering 40

Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. To make accurate conclusions based on the analysis of the data, you need to understand what that data represents in the first place.

Data Science 97

Data Science BI Data Mining Business Intelligence 97

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

APRIL 8, 2015

The open source framework hadoop is somewhat immature and big data analytics companies are now eyeing on Hadoop vendors- a growing community that delivers robust capabilities, tools and innovations for improvised commercial hadoop big data solutions. billion by 2020. billion by 2020.

Hadoop 40

Hadoop Big Data Data Solutions Amazon Web Services 40

AltexSoft

FEBRUARY 11, 2023

The former uses data to generate insights and help businesses make better decisions, while the latter designs data frameworks, flows, standards, and policies that facilitate effective data analysis. But first, all candidates must be accredited by Arcitura as Big Data professionals.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JUNE 6, 2025

Data Storage- Exploring various data storage options, including Azure SQL Database, Azure Cosmos DB , Azure Blob Storage , and Azure Data Lake Storage. Data Processing- Learning about data processing technologies, such as Azure Data Factory , Azure Databricks , and Azure Stream Analytics.

Certification 40

Certification Cloud Cloud Computing SQL 40

Knowledge Hut

SEPTEMBER 6, 2023

To obtain a data science certification, candidates typically need to complete a series of courses or modules covering topics like programming, statistics, data manipulation, machine learning algorithms, and data analysis. Some of the most popular database management tools in the industry are NoSql, MongoDB and oracle.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

ProjectPro

NOVEMBER 10, 2016

Candidates can master Hadoop skills by working on hands-on projects which can be appealing to companies who are looking to scrutinize candidates on their ability to deliver real-world big data solutions. 5) 28% of Hadoopers possess NoSQL database skills.

Hadoop 52

Hadoop NoSQL Java Electronics 52

Knowledge Hut

DECEMBER 26, 2023

IBM is the leading supplier of Big Data-related products and services. IBM Big Data solutions include features such as data storage, data management, and data analysis. It also provides Big Data products, the most notable of which is Hadoop-based Elastic MapReduce.

Big Data 52

Big Data Amazon Web Services Unstructured Data Manufacturing 52

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. It is also considered among the important big data consulting firms.

Big Data 52

Big Data Consulting Amazon Web Services Hadoop 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Transportation 52

Knowledge Hut

NOVEMBER 19, 2023

Benefits of Azure Data Engineer Tools Azure tools for Data Engineers offer several benefits for organizations and professionals involved in data engineering: Scalability: Azure data services can scale elastically to handle growing data volumes and workloads, ensuring that your data solutions remain performant as your needs expand.

Data Engineer 52

Data Engineer Data Engineering Engineering PostgreSQL 52

Cloud Academy

JANUARY 27, 2022

Some basic real-world examples are: Relational, SQL database: e.g. Microsoft SQL Server Document-oriented database: MongoDB (classified as NoSQL) The Basics of Data Management, Data Manipulation and Data Modeling This learning path focuses on common data formats and interfaces.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

OCTOBER 8, 2023

Exam Format: Aspirants need a scaled score of 750 on 65 questions with questions based on 20% Data Engineering, 24% Exploratory Data Analysis, 36% Modeling, and 20% Machine Learning Implementation and Operations. Eligibility: This exam is for aspirants who are well-versed in databases and DB solutions.

AWS 52

AWS Certification Cloud Computing Architecture 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 Generalist 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. AWS' principal computing solution is its EC2 instances, which offer flexible computing on request and can be tailored for various applications. over the next decade.

AWS 45

AWS Cloud Amazon Web Services Cloud Computing 45

Databand.ai

DECEMBER 13, 2022

She publishes a popular blog on Medium , featuring advice for data engineers and posts frequently on LinkedIn about coding and data engineering. He is also an AWS Certified Solutions Architect and AWS Certified Big Data expert.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Knowledge Hut

DECEMBER 27, 2023

This NoSQL, document-oriented database is written in C, C++, and JavaScript. Based on a Thor architecture, this open-source tool offers a good substitute for Hadoop and some other big data platforms as well. Unleash the power of data with our immersive Data Analysis Bootcamp.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

ProjectPro

JUNE 6, 2025

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

Edureka

MAY 27, 2025

Explain the use of Amazon DynamoDB Accelerator (DAX) in data engineering applications. Amazon DynamoDB Accelerator (DAX) is a caching service that operates in memory for DynamoDB, a NoSQL database. It can enhance data engineering applications by speeding up read access to DynamoDB tables.

AWS 40

AWS Data Engineer Data Engineering Engineering 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

ProjectPro

JUNE 6, 2025

Here begins the journey through big data in healthcare highlighting the prominently used applications of big data in healthcare industry. This data was mostly generated by various regulatory requirements, record keeping, compliance and patient care. trillion towards healthcare data solutions in the Healthcare industry.

Healthcare 45

Healthcare Big Data Hospitality Project 45

ProjectPro

MARCH 16, 2015

Here begins the journey through big data in healthcare highlighting the prominently used applications of big data in healthcare industry. This data was mostly generated by various regulatory requirements, record keeping, compliance and patient care. trillion towards healthcare data solutions in the Healthcare industry.

Healthcare 40

Healthcare Big Data Hospitality Project 40