ProjectPro

FEBRUARY 16, 2023

It also covers core concepts, including in-memory caching, interactive shells, Spark RDDs, and distributed datasets. Big Data Analytics with Spark by Mohammed Guller This book is an ideal fit if you're looking for fundamental analytics and machine learning with Spark.

Big Data 52

Big Data Scala Machine Learning Hadoop 52

Data Science Blog: Data Engineering

JULY 4, 2022

Already familiar with the term big data, right? Despite the fact that we would all discuss Big Data, it takes a very long time before you confront it in your career. Apache Spark is a Big Data tool that aims to handle large datasets in a parallel and distributed manner.

Hadoop 52

Hadoop Big Data Datasets Scala 52

Knowledge Hut

SEPTEMBER 25, 2023

With the ever-growing importance of data, individuals with expertise in data analysis are in high demand, and a plethora of exciting job opportunities await them. Data analysis courses can also support your argument for a wage increase or promotion by demonstrating that you can add more value as a data analyst.

Certification 52

Certification Business Analyst Big Data Data Analysis 52

AltexSoft

FEBRUARY 11, 2023

The former uses data to generate insights and help businesses make better decisions, while the latter designs data frameworks, flows, standards, and policies that facilitate effective data analysis. But first, all candidates must be accredited by Arcitura as Big Data professionals.

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

FEBRUARY 5, 2022

And, when one uses statistical tools over these data points to estimate their values in the future, it is called time series analysis and forecasting. The statistical tools that assist in forecasting a time series are called the time series forecasting models. So, how can data analysis tools help us?

Deep Learning 52

Deep Learning Datasets Python Machine Learning 52

ProjectPro

DECEMBER 7, 2021

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JUNE 20, 2023

The ML engineers act as a bridge between software engineering and data science. They take raw data from the pipelines and enhance programming frameworks using the big data tools that are now accessible. They transform unstructured data into scalable models for data science.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

AltexSoft

JUNE 7, 2021

Apache Hadoop is an open-source framework written in Java for distributed storage and processing of huge datasets. The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Databand.ai

DECEMBER 13, 2022

With more than five years of experience as a data engineer, Sarah currently works at Zwift, where she leads a team of vendors to build data pipelines and deploy machine learning models and owns e-commerce datasets to handle data quality, data contracts, and resolve pipeline downtime.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

ProjectPro

APRIL 20, 2017

These Hadoop projects come with detailed understanding of the problem statement, source code, dataset and a video tutorial explaining the entire solution. Users will work on the Million Song Dataset released by the Columbia University’s Lab for Recognition and Organization of Speech and Audio.

Hadoop 40

Hadoop Big Data Coding Project 40

ProjectPro

NOVEMBER 14, 2015

These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. These Apache Spark projects are mostly into link prediction, cloud hosting, data analysis, and speech analysis. Data Integration 3.Scalability Specialized Data Analytics 7.Streaming

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

DECEMBER 14, 2021

Customer Churn Analysis 2. Product Sales Data Analysis 3. Marketing Campaign Insights Analysis 4. Financial Performance Analysis 5. Healthcare Sales Analysis Intermediate-Level Power BI Project Ideas 6. Loan Application Analysis 10. Airport Authority Data Analysis 12.

BI 52

BI Project Business Intelligence Datasets 52

ProjectPro

JANUARY 25, 2022

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

JANUARY 24, 2023

It’s ability to handle large volumes of data and provide real-time insights makes it a goldmine for organization looking to leverage data analytics for competitive advantage. Use any e-commerce dataset from Kaggle for creating this dashboard. Use the remote working survey dataset from Kaggle for building this dashboard.

Project 52

Project Data Mining Big Data Big Data Tools 52

Cloudera

APRIL 15, 2022

“As the availability and volume of Earth data grow, researchers spend more time downloading and processing their data than doing science,” according to the NCSS website. In Europe, for instance, this data is driving a strong sustainability effort to create a carbon-neutral continent.

Big Data Tools 80

Big Data Tools Big Data Banking Finance 80

ProjectPro

NOVEMBER 30, 2021

Project Idea: In this project, you will work on a retail store’s data and learn how to realize the association between different products. Additionally, you will learn how to implement Apriori and Fpgrowth algorithms over the given dataset. The goal is to predict the sales and revenue of different stores based on historical data.

Business Analyst 52

Business Analyst Project Retail Datasets 52

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. Conclusion Data analysis requires scalable, adaptable, and high-performance tools to quickly provide insights as data volumes grow.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

ProjectPro

JANUARY 24, 2023

Data Flow in ADF Example Imagine you are working for a retail company that wants to analyze customer and sales data across various platforms for better business decision-making to improve sales. The next step would be to transform it and load it into a data warehouse for further analysis.

Retail 52

Retail Big Data Data Pipeline Media 52

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 11, 2021

Data Lake vs Data Warehouse - The Differences Before we closely analyse some of the key differences between a data lake and a data warehouse, it is important to have an in depth understanding of what a data warehouse and data lake is. Data Lake vs Data Warehouse - The Introduction What is a Data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

JUNE 24, 2021

Here are a few reasons why you should work on data analytics projects: Data analytics projects for grad students can help them learn big data analytics by doing instead of just gaining theoretical knowledge. This gives an evaluation criteria for the government as well to understand how the citizens are compensated.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

JANUARY 31, 2023

The end of a data block points to the location of the next chunk of data blocks. DataNodes store data blocks, whereas NameNodes store these data blocks. Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples. What is MapReduce in Hadoop?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

OCTOBER 30, 2023

It is the ideal moment to begin working on your big data project if you are a big data student in your final year. Current suggestions for your next big data project are provided in this article. Why Are Big Data Projects So Important? Enroll now!

Big Data 52

Big Data Coding Project Medical 52

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

APRIL 15, 2016

Modes of Execution for Apache Pig Frequently Asked Apache Pig Interview Questions and Answers Before the advent of Apache Pig, the only way to process huge volumes of data stores on HDFS was - Java based MapReduce programming. Ace Your Next Job Interview with Mock Interviews from Experts to Improve Your Skills and Boost Confidence!

Hadoop 40

Hadoop Java Big Data SQL 40

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.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 21, 2015

IBM has a nice, simple explanation for the four critical features of big data: a) Volume –Scale of data b) Velocity –Analysis of streaming data c) Variety – Different forms of data d) Veracity –Uncertainty of data Here is an explanatory video on the four V’s of Big Data 3.

Hadoop 40

Hadoop Big Data Metadata Unstructured Data 40

ProjectPro

APRIL 1, 2017

Source : [link] ) Big Data Tool For Trump’s Big Government Immigration Plans. Large volumes of data is generated by various electronic devices used in different end use segments like Retail, Banking, Finance, Insurance, Healthcare and public utilities.

Hadoop 40

Hadoop Data Lake Electronics Big Data 40