ProjectPro

SEPTEMBER 9, 2021

Hive , for instance, does not support sub-queries and unstructured data. Data update and deletion operations are also not possible with Hive. The tool also has acceptable latency for interactive data browsing, and it causes adverse implications on the overall performance.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Knowledge Hut

MARCH 26, 2024

Data Solutions Architect Role Overview: Design and implement data management, storage, and analytics solutions to meet business requirements and enable data-driven decision-making. Role Level: Mid to senior-level position requiring expertise in data architecture, database technologies, and analytics platforms.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

Knowledge Hut

NOVEMBER 16, 2023

More and more companies are focusing on hiring data scientists to help them unlock the true potential of their businesses and channelize maximum profits. A data scientist is a person expert in analytics, especially gathering and evaluating large chunks of structured and unstructured data to find trends and proper data management.

IT 52

IT Software Engineer Software Engineering Cloud Computing 52

Knowledge Hut

JANUARY 24, 2024

Beyond their analytical prowess, they possess the ability to uncover, refine, and present data effectively. They excel in handling unstructured data, a crucial asset for businesses in today's data-driven landscape. A career in data science holds immense promise, with abundant opportunities and attractive salaries.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

ProjectPro

SEPTEMBER 26, 2021

Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. You must also work on soft skills alongside the expansion of your technical expertise.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

JULY 26, 2023

These datasets typically involve high volume, velocity, variety, and veracity, which are often referred to as the 4 v's of Big Data: Volume: Volume refers to the vast amount of data generated and collected from various sources. Managing and analyzing such large volumes of data requires specialized tools and technologies.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 52

NoSQL Database Hadoop Big Data 52

AltexSoft

MAY 14, 2021

What is Big Data analytics? Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools. The best way to understand the idea behind Big Data analytics is to put it against regular data analytics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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. Issues with small files.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

APRIL 1, 2016

GlobeNewsWire.com Cloudera – the global provider of the easiest and the most secure data management to be built of Apache Hadoop , recently announced that recently it has moved from the Challengers to the Visionaries position in the 2016 Gartner Magic Quadrant for Data Warehouse and Data Management solution for analytics.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

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

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 26, 2015

1997 -The term “BIG DATA” was used for the first time- A paper on Visualization published by David Ellsworth and Michael Cox of NASA’s Ames Research Centre mentioned about the challenges in working with large unstructured data sets with the existing computing systems. Truskowski. Let us know in comments below!

Big Data 40

Big Data Unstructured Data Hadoop NoSQL 40

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

SEPTEMBER 14, 2016

The better a hadoop developer knows the data, the better they know what kind of results are possible with that amount of data. Concisely, a hadoop developer plays with the data, transforms it, decodes it and ensure that it is not destroyed. Managing Hadoop jobs using scheduler. Reviewing and managing hadoop log files.

Hadoop 40

Hadoop Unstructured Data Java Big Data 40

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 Lake 40

Data Lake Data Warehouse Hadoop Unstructured 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

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 AWS Relational Database 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 2- Internal Data transformation at LakeHouse.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

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 Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 30, 2021

Cloud storage is the best option for storing all the processed data, and it is secure and easily accessible, and no infrastructure is required. It is the most feasible option when the data size is huge. For instance, specify the list of country codes allowed in a country data field.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

MAY 5, 2023

Revenue management teams can anticipate future demand more accurately, and therefore predict the optimal pricing model for their entire portfolio — across all channels, in real-time.” This reduces the need for on-site visits while maintaining high-quality standards across property portfolios.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

ProjectPro

JUNE 18, 2015

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Organizations with on-premise or in cloud big data managements systems will not merely have to invest in hardware or software costs but also will have to incur various other significant startup costs.

Big Data 52

Big Data Process Data Cleanse Data Analytics 52

ProjectPro

MARCH 23, 2016

Hadoop has become the go-to big data technology because of its power for processing large amounts of semi-structured and unstructured data. Hadoop is not popular for its processing speed in dealing with small data sets. Check Out Apache Hive Real Time Projects to Build Your Portfolio How to use Hadoop?

Hadoop 40

Hadoop IT Big Data Retail 40

ProjectPro

FEBRUARY 8, 2017

However, this does not mean just Hadoop but Hadoop along with other big data technologies like in-memory frameworks, data marts, discovery tools ,data warehouses and others that are required to deliver the data to the right place at right time. We are looking forward to what 2017 will bring on to the big data table.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

MARCH 16, 2015

McKinsey projects that the use of Big Data in healthcare can reduce the healthcare data management expenses by $300 billion -$500 billion. Big Data in healthcare originates from the large electronic health datasets – these datasets are very difficult to manage with the conventional hardware and software.

Healthcare 40

Healthcare Big Data Project Hospitality 40

ProjectPro

MARCH 21, 2016

Organizations run critical applications on Mainframe systems, which generate huge volumes of data but lack the capability to support novel business requirements of processing unstructured data and also involve huge maintenance costs. This is the best time for mainframe professionals to start updating their skillset with Hadoop.

Hadoop 40

Hadoop Insurance Big Data Retail 40

Knowledge Hut

FEBRUARY 7, 2023

Integrate multiple data science tools The most important feature of these platforms is integrating all the tools in one place so that all the work like data cleaning, analysis, modeling, and deployment can be done with ease, and also this will fasten the process. What Makes a Data Science Platform Valuable?

Data Science 52

Data Science Google Cloud AWS Programming Language 52

ProjectPro

JUNE 24, 2021

Exploring various big data projects gives a better idea of where your interests lie while working with different analytics tools. It helps to build a job-winning data analytics portfolio and sets you apart from other candidates while applying for a job. They are central repositories of data integrated from various sources.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

AUGUST 11, 2021

Storage Layer: This is a centralized repository where all the data loaded into the data lake is stored. HDFS is a cost-effective solution for the storage layer since it supports storage and querying of both structured and unstructured data. A Data lake cannot be a direct replacement for a data warehouse.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

SEPTEMBER 26, 2014

BI professionals use various tools to draw useful data that are used to generate customized reports and this is where the Hadoop File Distribution System (HDFS) proves itself. This situation in turn suggests that BI professionals have to learn Hadoop.

Business Intelligence 40

Business Intelligence Hadoop BI Relational Database 40

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.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

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. The workflows in Oozie are executed based on data and time dependencies.

Hadoop 52

Hadoop Architecture IT Java 52

ProjectPro

JUNE 2, 2015

It is difficult to make sense out of billions of unstructured data points (in the form of news articles, forum comments, and social media data) without powerful technologies like Hadoop, Spark and NoSQL in place. of marketers believe that they have the right big data talent.

Big Data 40

Big Data Hadoop Banking Retail 40

U-Next

OCTOBER 26, 2022

Risk Management . AI assesses unstructured data about potentially dangerous actions or activities in an organization’s operations. AI supports managers in managing investment portfolios and assures logical, data-driven decision-making. Portfolio Development . Financial Advice .

Finance 40

Finance Portfolio Banking Algorithm 40

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