ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. MapReduce is a Hadoop framework used for processing large datasets.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Edureka

AUGUST 27, 2024

AWS Quicksight can pull data from multiple sources, such as individual databases, data warehouses, and SaaS sources, unlike other BI tools. It supports numerous file formats, including semi-structured JSON format. It means you can gather structured and semi-structured data from any source to derive business intelligence.

BI 52

BI Business Intelligence AWS Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

It leverages a Massively Parallel Processing (MPP) architecture, which is optimized for executing complex analytical queries on large datasets efficiently. This makes it an excellent choice for organizations that need to analyze large volumes of structured and semi-structured data quickly and effectively.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

ProjectPro

JANUARY 31, 2022

Databricks Snowflake Projects for Practice in 2022 Dive Deeper Into The Snowflake Architecture FAQs on Snowflake Architecture Snowflake Overview and Architecture With Data Explosion, acquiring, processing, and storing large or complicated datasets appears more challenging. Snowflake offers no built-in virtual private networking.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. Multi-node, multi-GPU deployments are also supported by RAPIDS, allowing for substantially faster processing and training on much bigger datasets. It offers a fault-tolerant storage engine that prioritizes data security.

Big Data 52

Big Data Project Metadata Programming Language 52

Rockset

FEBRUARY 25, 2021

Analyze Semi-Structured Data As Is The data feeding modern applications is rarely in neat little tables. Instead, this data is often semi-structured in JSON or arrays. From there, you can join and aggregate data without using complex code.

SQL 40

SQL Data Pipeline Kafka Database 40

ProjectPro

APRIL 27, 2016

Pig Hadoop dominates the big data infrastructure at Yahoo as 60% of the processing happens through Apache Pig Scripts. Get More Practice, More Big Data and Analytics Projects , and More guidance.Fast-Track Your Career Transition with ProjectPro HBase To provide timely search results across the Internet, Google has to cache the web.

Hadoop 40

Hadoop Big Data Technology Big Data Tools 40

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Kicking off a big data analytics project is always the most challenging part.

Big Data 52

Big Data Coding Project Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts. Key Benefits and Takeaways Learn the basics of big data with Spark.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

AltexSoft

DECEMBER 15, 2021

Namely, AutoML takes care of routine operations within data preparation, feature extraction, model optimization during the training process, and model selection. In the meantime, we’ll focus on AutoML which drives a considerable part of the MLOps cycle, from data preparation to model validation and getting it ready for deployment.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

Edureka

JULY 4, 2024

On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. The platform’s massive parallel processing (MPP) architecture empowers you with high-performance querying of even massive datasets.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

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 BI Machine Learning 64