Cloudera

SEPTEMBER 15, 2022

It was designed as a native object store to provide extreme scale, performance, and reliability to handle multiple analytics workloads using either S3 API or the traditional Hadoop API. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 92

Systems Hadoop Metadata Telecommunication 92

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

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 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 ETL Tools Unstructured Data ETL System 52

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

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 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 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

Knowledge Hut

DECEMBER 21, 2023

To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. Hadoop tools are frameworks that help to process massive amounts of data and perform computation. You can learn in detail about Hadoop tools and technologies through a Big Data and Hadoop training online course.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 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

U-Next

MARCH 1, 2023

A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

ProjectPro

SEPTEMBER 14, 2016

A lot of people who wish to learn hadoop have several questions regarding a hadoop developer job role - What are typical tasks for a Hadoop developer? How much java coding is involved in hadoop development job ? What day to day activities does a hadoop developer do? Table of Contents Who is a Hadoop Developer?

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

MAY 13, 2016

Hadoop is the most talked about innovation in the IT industry that has shaken the entire data centre infrastructure at many organizations. As the appetite for Hadoop and related big data technologies grows at an exponential rate, it is not out to spell the death of data warehousing.

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40

ProjectPro

APRIL 4, 2015

With the help of our best in class Hadoop faculty, we have gathered top Hadoop developer interview questions that will help you get through your next Hadoop job interview. IT organizations from various domains are investing in big data technologies, increasing the demand for technically competent Hadoop developers.

Hadoop 40

Hadoop Big Data Recruitment Java 40

ProjectPro

APRIL 27, 2016

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks said - "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward. Curious to know about these Hadoop innovations?

Hadoop 40

Hadoop Big Data Technology Kafka 40

ProjectPro

NOVEMBER 11, 2014

Confused over which framework to choose for big data processing - Hadoop MapReduce vs. Apache Spark. This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem.

Hadoop 40

Hadoop Machine Learning Scala Big Data 40

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

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

Towards Data Science

JANUARY 16, 2024

New data formats emerged — JSON, Avro, Parquet, XML etc. Result: Hadoop & NoSQL frameworks emerged. Data lakes were introduced to store the new data formats. Examples include: Amazon Redshift, Google BigQuery, Snowflake, Azure Synapse Analytics, Databricks etc. So what was missing?

Data Warehouse 63

Data Warehouse Data Architecture Relational Database NoSQL 63

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 52

Big Data Hadoop Relational Database AWS 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

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

JULY 18, 2023

Whether you’re a data scientist, software engineer, or big data enthusiast, get ready to explore the universe of Apache Spark and learn ways to utilize its strengths to the fullest. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

APRIL 23, 2024

So, before you choose a field, it is essential to go for Business Intelligence and Visualization online certification and learn to turn data into opportunities with BI and visualization. The analytics domain gets classified into three categories, with data analytics being the broader term.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. As a result, a data lake concept becomes a game-changer in the field of big data management. . Data is kept in its.raw format. Different Storage Options .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

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

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

ProjectPro

AUGUST 24, 2016

In spite of a few rough edges, HBase has become a shining sensation within the white hot Hadoop market. However, Hadoop cannot handle high velocity of random writes and reads and also cannot change a file without completely rewriting it. HBase provides real-time read or write access to data in HDFS.

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

MARCH 19, 2015

With increasing size of the database or increasing number of users, Relational Database Management Systems using SQL suffer from serious performance bottlenecks -making real time unstructured data processing a hard row to hoe. NoSQL databases can also store and process data in real time - something that SQL is not capable of doing it.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

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

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. It does away with the requirement to import data from an outside source.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

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

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 Data Science Data Analytics Cloud Computing 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