ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database AWS 52

AltexSoft

JUNE 7, 2021

Main users of Hive are data analysts who work with structured data stored in the HDFS or HBase. Data management and monitoring options. Among solutions facilitation data management are. RDD easily handles both structured and unstructured data. Netflix for near real-time movie recommendations.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

NOVEMBER 17, 2021

Building a portfolio of projects will give you the hands-on experience and skills required for performing sentiment analysis. It'll be a great addition to your data science portfolio (or CV) as well. Over the years, analyses were mostly limited to structured data within organizations.

Coding 52

Coding Project Entertainment Datasets 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

ProjectPro

SEPTEMBER 30, 2014

While the initial era of ETL ignited enough sparks and got everyone to sit up, take notice and applaud its capabilities, its usability in the era of Big Data is increasingly coming under the scanner as the CIOs start taking note of its limitations.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

ProjectPro

MARCH 15, 2016

These days we notice that many banks compile separate data warehouses into a single repository backed by Hadoop for quick and easy analysis. Hadoop clusters are used by banks to create more accurate risk analysis models for the customers in its portfolio. Hadoop allows us to store data that we never stored before.

Hadoop 40

Hadoop Retail Healthcare Banking 40

ProjectPro

OCTOBER 15, 2014

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

ProjectPro

SEPTEMBER 14, 2016

Concisely, a hadoop developer plays with the data, transforms it, decodes it and ensure that it is not destroyed. Most of the hadoop developers receive unstructured data through flume or structured data through RDBMS and perform data cleaning using various tools in the hadoop ecosystem.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

ProjectPro

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

MARCH 17, 2021

Deep learning models usually perform Classification tasks directly from sound, text, or images (unstructured data). Data is the governor when it comes to deciding on choosing between deep learning and machine learning. Build a Job-Winning Data Science Portfolio.

Deep Learning 52

Deep Learning Machine Learning Algorithm Data Science 52

ProjectPro

MAY 13, 2016

A data warehouse makes the best use of relational and structured data whereas Hadoop excels in storing and managing unstructured data - which traditional data warehouses cannot handle. Using a Hadoop-only strategy can prove to be dangerous for any business’s data needs.

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40

ProjectPro

JUNE 6, 2015

We know that data warehouse is very big and a very complicated tool to maintain and to meet Big Data problems. In BI we just consider structured data. We never imagined that we can also analyze some videos or logs or similar semi-structured data. We just focused on structured data on the databases.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

AUGUST 24, 2016

Table of Contents Need for HBase HBase –Understanding the Basics HBase Architecture Explained Components of Apache HBase Architecture HMaster Region Server Zookeeper Need for HBase Apache Hadoop has gained popularity in the big data space for storing, managing and processing big data as it can handle high volume of multi-structured data.

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

JANUARY 24, 2023

Additionally, columnar storage allows BigQuery to compress data more effectively, which helps to reduce storage costs. BigQuery enables users to store data in tables, allowing them to quickly and easily access their data. It supports structured and unstructured data, allowing users to work with various formats.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

ProjectPro

SEPTEMBER 26, 2014

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

ProjectPro

OCTOBER 18, 2021

From the outset of machine learning, it was challenging to work with unstructured data (image dataset) and transform it into structured data (texts). To build an outstanding portfolio, here are some of the essential points associated with the ML project that you have to showcase.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

ProjectPro

SEPTEMBER 11, 2015

Learning Hadoop will ensure that you can build a secure career in Big Data. Big Data is not going to go away. There will always be a place for RDBMS, ETL, EDW and BI for structured data. But at the pace and nature at which big data is growing, technologies like Hadoop will be very necessary to tackle this data.

Hadoop 52

Hadoop Java BI Big Data 52

ProjectPro

MAY 20, 2015

Several big data companies are looking to tame the zettabyte’s of BIG big data with analytics solutions that will help their customers turn it all in meaningful insights. .”-said Palantir Metropolis- This product focusses on information management, data integration and quantitative analytics.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

DECEMBER 10, 2021

Azure Blob storage is a Microsoft storage offering that is meant explicitly for cloud objects and is suitable for holding vast quantities of unstructured data. Unstructured data, such as text or binary data, does not correspond to a specific data model or description. Explain Azure Blob storage.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

APRIL 4, 2015

Random Job Distribution Coordinate resource management Self managed resources and worker Process Structured and Semi-Structured Data. Process Unstructured Data. Build a Big Data Project Portfolio by working on ProjectPro's Hadoop Mini Projects 9) What is distributed cache and what are its benefits?

Hadoop 40

Hadoop Big Data Recruitment Java 40

Knowledge Hut

JANUARY 11, 2024

It uses complex machine learning algorithms to build meaningful and structured data. Data Science can be described as a domain that applies advanced analytics, statistics and scientific principle for extracting valuable information and deriving valuable conclusions from structured or unstructured data.

Finance 93

Finance Data Science Programming Language Machine Learning 93

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

AUGUST 6, 2015

Companies like Electronic Arts, Riot Games are using big data for keeping a track of game play which helps predict performance of the play by analysing 4TB of operational logs and 500GB of structured data. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Hadoop Insurance Media 52

ProjectPro

JUNE 4, 2015

In our earlier articles, we have defined “What is Apache Hadoop” To recap, Apache Hadoop is a distributed computing open source framework for storing and processing huge unstructured datasets distributed across different clusters. It can also be used for exporting data from Hadoop o other external structured data stores.

Hadoop 52

Hadoop Architecture IT Java 52

ThoughtSpot

SEPTEMBER 26, 2024

With ThoughtSpot Embedded, we are also rapidly adding tech startups and enterprises in our portfolio as they bring our search and AI-driven analytics capabilities into their SaaS apps and other business applications.

Electronics 59

Electronics Unstructured Data Recruitment Portfolio 59

Knowledge Hut

DECEMBER 13, 2023

HData Systems At HData Systems, we develop unique data analysis tools that break down massive data and turn it into knowledge that is useful to your company. Then, using both structured and unstructured data, we transform them into easily observable measures to assist you in choosing the best options for your company.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

AltexSoft

DECEMBER 15, 2021

The software will make this choice itself, picking from the existing portfolio of options the one fitting your task best. Currently, the enterprise platform works with both structured and unstructured data and automatically pre-tailored deep learning algorithms, concentrating on AI explainability. Algorithm selection.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

ProjectPro

MARCH 14, 2014

In 2015, big data has evolved beyond the hype. 87% of companies using big data believe that within next 3 years big data analytics will redefine the competitive landscape of various industries. Work on Interesting Big Data and Hadoop Projects to build an impressive project portfolio! How big data helps businesses?

Hadoop 40

Hadoop Big Data Data Mining Retail 40