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 Java Unstructured Data SQL 52

Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

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

U-Next

MARCH 7, 2023

ntroduction Data Analytics is an extremely important field in today’s business world, and it will only become more so as time goes on. By 2023, Data Analytics is projected to be worth USD 240.56 Statistics, linear algebra, and calculus are generally required for Data Analysts. What is data extraction?

Data Mining 96

Data Mining Scala Government Data Governance 96

ProjectPro

JULY 3, 2015

SAP is all set to ensure that big data market knows its hip to the trend with its new announcement at a conference in San Francisco that it will embrace Hadoop. What follows is an elaborate explanation on how SAP and Hadoop together can bring in novel big data solutions to the enterprise.

Hadoop 40

Hadoop Big Data Data Solutions Unstructured Data 40

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Kafka 40

Knowledge Hut

MARCH 18, 2024

Thinking about working as a data analyst or project manager? Both data analytics and project management are pivotal fields in the business world, with data analysts and project managers each fulfilling indispensable roles within their respective domains. What is Data Analytics? What is Project Management?

Data Analytics 52

Data Analytics Project Management Programming Language 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. ® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). However, Apache Kafka is more than just messaging.

Kafka 21

Kafka SQL BI Hadoop 21

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

MARCH 14, 2014

Every department of an organization including marketing, finance and HR are now getting direct access to their own data. This is creating a huge job opportunity and there is an urgent requirement for the professionals to master Big Data Hadoop skills. In 2015, big data has evolved beyond the hype.

Hadoop 40

Hadoop Big Data Data Mining Retail 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

Edureka

APRIL 17, 2023

Data analytics is the process of analyzing, interpreting, and presenting data in a meaningful way. In today’s data-driven world, data analytics plays a critical role in helping businesses make informed decisions. This article will discuss nine data analytics project ideas for your portfolio.

Portfolio 40

Portfolio Data Analytics Project Data Mining 40

Knowledge Hut

SEPTEMBER 6, 2023

It will help you master the skill of deriving insights from raw data and use cutting edge tools to develop models which can help in making viable business decisions. Data Science Bootcamp course from KnowledgeHut will help you gain knowledge on different data engineering concepts. Expiration - No expiry 8.

Data Science 97

Data Science Certification Business Analyst Machine Learning 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

Cloud Academy

JANUARY 27, 2022

A data engineer is an engineer who creates solutions from raw data. A data engineer develops, constructs, tests, and maintains data architectures. Let’s review some of the big picture concepts as well finer details about being a data engineer. Earlier we mentioned ETL or extract, transform, load.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. There are several widely used unstructured data storage solutions such as data lakes (e.g.,

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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 26, 2021

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

U-Next

SEPTEMBER 7, 2022

Autonomous data warehouse from Oracle. . What is Data Lake? . Essentially, a data lake is a repository of raw data from disparate sources. A data lake stores current and historical data similar to a data warehouse. Data Lake Vs. Data Warehouse: Latest Industry Stats .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

APRIL 23, 2024

Data Science is the field that focuses on gathering data from multiple sources using different tools and techniques. Whereas, Business Intelligence is the set of technologies and applications that are helpful in drawing meaningful information from raw data. Hence, the average salary of a BI analyst is $ 96, 100.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

AUGUST 25, 2023

Data warehouses are often the most sensible choice for data platforms whose primary use case is for data analysis and reporting. With pre-built functionalities and robust SQL support, data warehouses are tailor-made to enable swift, actionable querying for data analytics teams working primarily with structured data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 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

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

DECEMBER 7, 2021

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data. ETL is the acronym for Extract, Transform, and Load.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JANUARY 18, 2024

SQL for data migration 2. The role can also be defined as someone who has the knowledge and skills to generate findings and insights from available raw data. Data Engineer A professional who has expertise in data engineering and programming to collect and covert raw data and build systems that can be usable by the business.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? Since vast amounts of data is present in a data lake, it is ideal for tracking analytical performance and data integration. Recommended Reading: Is Hadoop Going To Replace Data Warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Edureka

AUGUST 2, 2023

Data scientists can use SQL to write queries that get particular subsets of data, join various tables, perform aggregations, and use sophisticated filtering methods. Data scientists can also organize unstructured raw data using SQL so that it can be analyzed with statistical and machine learning methods.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

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

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 27, 2023

A data engineer is a key member of an enterprise data analytics team and is responsible for handling, leading, optimizing, evaluating, and monitoring the acquisition, storage, and distribution of data across the enterprise. Data Engineers indulge in the whole data process, from data management to analysis.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Knowledge Hut

FEBRUARY 2, 2024

Amazon Web Services (AWS) Databases such as MYSQL and Hadoop Programming languages, Linux web servers and APIs Application programming and Data security Networking. Data Science Course The art and the science of data analytics have been in significant demand, as you would know if you’re an active user of any job portal.

Programming Language 98

Programming Language Amazon Web Services Java Cloud Computing 98

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake Machine Learning BI 64

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 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 Data Analytics 40

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52