Knowledge Hut

JANUARY 24, 2024

In their quest for knowledge, data scientists meticulously identify pertinent questions that require answers and source the relevant data for analysis. Beyond their analytical prowess, they possess the ability to uncover, refine, and present data effectively.

Database-centric 52

Database-centric Data Science Machine Learning Datasets 52

Databand.ai

JULY 19, 2023

Learn more in our detailed guide to data lineage visualization (coming soon) Integration with Multiple Data Sources Data lineage tools are designed to integrate with a wide range of data sources, including databases, data warehouses, and cloud-based data platforms.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

ProjectPro

JULY 13, 2015

With more than 150 petabytes of data, approximately 3.5 billion user accounts and 30,000 databases, JPMorgan Chase is definitely a name to reckon with in the financial sector. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

ProjectPro

JUNE 1, 2017

Datos IO has extended its on-premise and public cloud data protection to RDBMS and Hadoop distributions. Its RecoverX distributed database backup product of latest version v2.0 Cloudera is more inclined on becoming a product centric business with 23% of its revenue coming from services past year in comparison to 31% for Hortonworks.

Hadoop 52

Hadoop Medical Pipeline-centric Database-centric 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are skilled professionals who lay the foundation of databases and architecture. Using database tools, they create a robust architecture and later implement the process to develop the database from zero. Data engineers who focus on databases work with data warehouses and develop different table schemas.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

MAY 19, 2015

5 Reasons to Learn Hadoop ​ Hadoop brings in better career opportunities in 2015 Learn Hadoop to pace up with the exponentially growing Big Data Market Increased Number of Hadoop Jobs Learn Hadoop to Make Big Money with Big Data Hadoop Jobs Learn Hadoop to pace up with the increased adoption of Hadoop by Big data companies Why learn Hadoop?

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

Knowledge Hut

SEPTEMBER 26, 2023

It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. This cloud-centric approach ensures scalability, flexibility, and cost-efficiency for your data workloads.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. But what does that mean for the roles of data engineers and data scientists going forward?

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. Some examples of Big Data: 1. Pros: Reliable, low-cost, easy to learn tool.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

AltexSoft

JUNE 7, 2021

MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data engineers who previously worked only with relational database management systems and SQL queries need training to take advantage of Hadoop. Data storage options. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

JULY 30, 2021

Compared to Cloud computing, Mobile computing is more customer-centric. Use cases are in-memory caches and open-source databases. These instances use their local storage to store data. They get used in NoSQL databases like Redis, MongoDB, data warehousing. Why use Cloud Computing?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40