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. Who is a Data Scientist?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

FEBRUARY 27, 2023

Data engineering is also about creating algorithms to access raw data, considering the company's or client's goals. Data engineers can communicate data trends and make sense of the data, which large and small organizations demand to perform major data engineer jobs in Singapore.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 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

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 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. Apache Spark. Apache Storm.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

FEBRUARY 7, 2023

We use different SAS statements for reading the data, cleaning and manipulating it in the data step prior to analyzing it. The raw data gets transformed into a SAS dataset during the data stage. With the data step procedure, we can import data, provide reports on variables, and perform a descriptive analysis. 

Data Science 52

Data Science Datasets SQL Data Mining 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop AWS Relational Database 52

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

AltexSoft

MAY 14, 2021

Big Data analytics processes and tools. Data ingestion. The process of identifying the sources and then getting Big Data varies from company to company. It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

JANUARY 18, 2024

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

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

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

U-Next

AUGUST 3, 2022

The Big Data age in the data domain has begun as businesses cope with petabyte and exabyte-sized amounts of data. Up until 2010, it was extremely difficult for companies to store data. Now that well-known technologies like Hadoop and others have resolved the storage issue, the emphasis is on information processing.

Retail 52

Retail Data Science Computer Science Entertainment 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. The process requires extracting data from diverse sources, typically via APIs.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

SEPTEMBER 23, 2022

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. To address these issues, Big Data technologies such as Hadoop were established.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52

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