ProjectPro

OCTOBER 31, 2016

Having complete diverse big data hadoop projects at ProjectPro, most of the students often have these questions in mind – “How to prepare for a Hadoop job interview?” ” “Where can I find real-time or scenario-based hadoop interview questions and answers for experienced?”

Hadoop 52

Hadoop Big Data Utilities NoSQL 52

ProjectPro

JANUARY 19, 2022

Good knowledge of various machine learning and deep learning algorithms will be a bonus. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. and their implementation on the cloud is a must for data engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JULY 15, 2021

You shall also use digital signatures and data encryption algorithms, such as Advanced Encryption Standard (AES), in the system. Data security and cloud computing are the areas focussed on this project. Diffie-Hellman key exchange is a suitable algorithm to carry out encryption and decryption.

Cloud Computing 40

Cloud Computing Cloud Project Banking 40

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 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Knowledge of Hadoop, Spark, and Kafka.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 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

ProjectPro

SEPTEMBER 26, 2021

You must be aware of Amazon Web Services (AWS) and the data warehousing concept to effectively store the data sets. Machine Learning: Big Data, Machine Learning, and Artificial Intelligence often go hand-in-hand. Data Scientists use ML algorithms to make predictions on the data sets.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? The distillation layer enables taking the data from the storage layer and converting it into structured data for easier analysis. Insights from the system may be used to process the data in different ways.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. How is Hadoop related to Big Data? Explain the difference between Hadoop and RDBMS.

Big Data 52

Big Data Hadoop AWS Relational Database 52

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 Metadata 40

ProjectPro

NOVEMBER 15, 2021

Contributing to an open-source big data project has numerous potential benefits for developers and data scientists, including acquiring new skills, interacting with the community, developing a solid network, and sharpening skillset. In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JANUARY 25, 2022

When it comes to data ingestion pipelines, PySpark has a lot of advantages. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. PySpark SQL provides all existing and new users with consistent shared access to various data sources such as Parquet, JSON, and many others.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

FEBRUARY 8, 2017

Here’s a sneak-peak into what big data leaders and CIO’s predict on the emerging big data trends for 2017. The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

JULY 21, 2021

Kafka is a commit- log/message-processing implementation that stresses data storage and retrieval more, with scalability and data redundancy. It implements an intelligent client/subscriber policy where the consumer is solely responsible for requesting and retrieving data from the broker. What is Kafka?

Kafka 52

Kafka Big Data Java Architecture 52

Knowledge Hut

JANUARY 18, 2024

The insights that are generated through this process of Data Science can enable businesses to identify new opportunities, increase operational efficiency and effectiveness, improve their current strategies to grow their portfolio, and strengthen their position in the market. Python libraries such as pandas, NumPy, plotly, etc.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

NOVEMBER 22, 2021

Instead of sending this information with each job, PySpark uses efficient broadcast algorithms to distribute broadcast variables among workers, lowering communication costs. The data is stored in HDFS (Hadoop Distributed File System), which takes a long time to retrieve. The process of shuffling corresponds to data transfers.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 24, 2023

Furthermore, BigQuery supports machine learning and artificial intelligence, allowing users to use machine learning models to analyze their data. BigQuery Storage BigQuery leverages a columnar storage format to efficiently store and query large amounts of data. Steps: Load the data into BigQuery.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

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

The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data. When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JANUARY 31, 2022

Snowflake provides data warehousing, processing, and analytical solutions that are significantly quicker, simpler to use, and more adaptable than traditional systems. Snowflake is not based on existing database systems or big data software platforms like Hadoop. Let us now understand the Snowflake data storage layer in detail.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. How do you Create a Good Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

JUNE 4, 2015

All the components of the Hadoop ecosystem, as explicit entities are evident. All the components of the Hadoop ecosystem, as explicit entities are evident. The holistic view of Hadoop architecture gives prominence to Hadoop common, Hadoop YARN, Hadoop Distributed File Systems (HDFS ) and Hadoop MapReduce of the Hadoop Ecosystem.

Hadoop 52

Hadoop Architecture IT Java 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