ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

ProjectPro

SEPTEMBER 30, 2014

Hadoop’s significance in data warehousing is progressing rapidly as a transitory platform for extract, transform, and load (ETL) processing. Mention about ETL and eyes glaze over Hadoop as a logical platform for data preparation and transformation as it allows them to manage huge volume, variety, and velocity of data flawlessly.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 52

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

SEPTEMBER 9, 2021

The datasets are usually present in Hadoop Distributed File Systems and other databases integrated with the platform. Hive is built on top of Hadoop and provides the measures to read, write, and manage the data. HQL or HiveQL is the query language in use with Apache Hive to perform querying and analytics activities.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

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

Knowledge Hut

JUNE 16, 2023

In today's data-driven world, organizations are trying to find valuable insights from the vast sets of data available to them. That is where Data analytics comes into the picture - guiding organizations to make smarter decisions by utilizing statistical and computational methods. What is Data Analytics?

Programming Language 52

Programming Language Cloud Computing Data Preparation Data Science 52

Edureka

AUGUST 2, 2023

It is a crucial tool for data scientists since it enables users to create, retrieve, edit, and delete data from databases.SQL (Structured Query Language) is indispensable when it comes to handling structured data stored in relational databases. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Monte Carlo

APRIL 24, 2023

AWS is one of the most popular data lake vendors. AWS Lake Formation offers an alternative for data teams looking for a more structured data lake or data lakehouse solution. The added structure and governance from Dataplex makes BigLake an intriguing data lakehouse option as well.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

OCTOBER 5, 2023

An AWS Big Data Specialist is an IT professional who efficiently designs, analyzes, and maintains data, has experience AWS analytics services, and has cleared the AWS Big Data Specialty certification exam. Besides AWS, you can also add Hadoop or Spark certifications to your merits.

Big Data 52

Big Data AWS Certification Amazon Web Services 52

ProjectPro

FEBRUARY 16, 2023

According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. Despite the buzz surrounding NoSQL , Hadoop , and other big data technologies, SQL remains the most dominant language for data operations among all tech companies.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

SEPTEMBER 26, 2021

Several industries across the globe are using Big Data tools and technology in their processes and operations. According to a study, the Big Data market in the banking sector will reach $62.10 Healthcare is another primary application area of Big Data analytics , and its market will touch $67.82 billion by 2025.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Rockset

JULY 6, 2022

After much internal debate, our team agreed to store every user event in Hadoop using a timestamp in a column named time_spent that had a resolution of a second. Data lakes built on NoSQL databases such as Hadoop are the best example of scaled-out data repositories of mixed types. This keeps the data intact.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Silectis

JANUARY 3, 2021

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

FEBRUARY 16, 2023

After the inception of databases like Hadoop and NoSQL, there's a constant rise in the requirement for processing unstructured or semi-structured data. Data Engineers are responsible for these tasks. However, when it comes to the best lucrative career, the USA is the preferred location.

Data Engineering 52

Data Engineering Data Engineer Engineering Healthcare 52

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades.

AWS 52

AWS Data Management ETL Tools Management 52

Knowledge Hut

NOVEMBER 28, 2023

As a result, most companies are transforming into data-driven organizations harnessing the power of big data. Here Data Science becomes relevant as it deals with converting unstructured and messy data into structured data sets for actionable business insights.

Data Architect 52

Data Architect Data Science Certification Big Data 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 6, 2015

Let’s take a look at how Amazon uses Big Data- Amazon has approximately 1 million hadoop clusters to support their risk management, affiliate network, website updates, machine learning systems and more. Sports brands like ESPN have also got on to the big data bandwagon. ” Interesting?

Big Data 52

Big Data Hadoop Insurance Media 52

Zalando Engineering

FEBRUARY 28, 2018

For the sake of comparison, let’s recap the Hadoop way of working: Hadoop saves intermediate states to disk and communicates over a network. Spark SQL for Structured data SQL is used for analytics but it's a pain to connect data processing pipelines like Spark or Hadoop to SQL database.

Data Analysis 40

Data Analysis Hadoop Datasets Scala 40

ProjectPro

JULY 22, 2016

The desire to save every bit and byte of data for future use, to make data-driven decisions is the key to staying ahead in the competitive world of business operations. All this is possible due to the low cost storage systems like Hadoop and Amazon S3. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

JUNE 6, 2015

Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. It replaced its traditional BI structure by integrating big data and Hadoop."-April So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. It can deliver near real-time analytics. Spark is a bit bare at the moment.

Scala 94

Scala Hadoop Datasets Java 94

ProjectPro

SEPTEMBER 1, 2015

” The most impressive thing about this is that mankind is capable of storing, processing and analysing this incredible bulk of data using open source frameworks like Hadoop in reasonable time. Once big data is loaded into Hadoop, what is the best way to use this data?

Hadoop 40

Hadoop Java Unstructured Data SQL 40

Knowledge Hut

NOVEMBER 28, 2023

The data goes through various stages, such as cleansing, processing, warehousing, and some other processes, before the data scientists start analyzing the data they have garnered. The data analysis stage is important as the data scientists extract value and knowledge from the processed, structured data.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

ProjectPro

MAY 20, 2015

It is difficult to stay up-to-date with the latest developments in IT industry especially in a fast growing area like big data where new big data companies, products and services pop up daily. With the explosion of Big Data, Big data analytics companies are rising above the rest to dominate the market.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

DECEMBER 26, 2023

Pipeline-centric Pipeline-centric data engineers work with Data Scientists to help use the collected data and mostly belong in midsize companies. Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 75

SQL Data Analytics Hadoop Raw Data 75

ProjectPro

MARCH 15, 2016

Hadoop is beginning to live up to its promise of being the backbone technology for Big Data storage and analytics. Companies across the globe have started to migrate their data into Hadoop to join the stalwarts who already adopted Hadoop a while ago. Hadoop runs on clusters of commodity servers.

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

MARCH 12, 2016

For the leading payment network - PayPal, Big Data is an asset and is used for serious business strategies. Big Data Analytics and Data Science is at the heart of all this processing in the 17-year-old PayPal. It also has online data - like how many people looked at a product, which website they visited, etc.

Big Data 52

Big Data Data Analytics Hadoop Algorithm 52