AltexSoft

JUNE 26, 2023

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

phData: Data Engineering

JANUARY 3, 2022

The big data analytics market is set to reach $103 billion by 2023 , with poor data quality costing the US economy up to $3.1 Fortune 1000 companies can gain more than $65 million additional net income, only by increasing their data accessibility by 10%. How do I audit and provision access? trillion yearly.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

ProjectPro

MARCH 17, 2014

All these facts clearly speak about the Big Data trend making waves in the market. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Image Credit: twitter.com There are hundreds of companies like Facebook, Twitter, and LinkedIn generating yottabytes of data.

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

FEBRUARY 8, 2017

The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol. In 2017, big data platforms that are just built only for hadoop will fail to continue and the ones that are data and source agnostic will survive.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

NOVEMBER 11, 2014

This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

Hadoop 40

Hadoop Scala Machine Learning Java 40

ProjectPro

JUNE 4, 2015

HDFS in Hadoop architecture provides high throughput access to application data and Hadoop MapReduce provides YARN based parallel processing of large data sets. The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis.

Hadoop 52

Hadoop Architecture IT Java 52