Concept & Main features_

Concept:
Capture, store, provide, analyze, view and share large volumes of data.

Great volume of data has been generated since we started recording information. With the recent spread of sensors and IoT, this data generation has become exponential.
The evolution of processing capacity and the new models of data organization allowed this huge volume of information – whether images, texts, sounds, social media posts and a multitude of formats – to be accessed, combined, compared and analyzed. quickly and transparently.

Main features:
The 7 Big Data “Vs”

Volume: Big data, usually at petabytes’ scale
Velocity: Data capture, processing and availability speed
Variety: More than different data sources, manage different formats and media
Veracity: Accuracy and reliability of embedded information
Variability: Different from Variety, deals with the understanding and interpretation of the data, based on its context.
Visualization: How data is presented, interpreted and consumed
Value: Value generation from the utilization of the lessons learned in data analysis and interpretation.

BigData is like teen sex

… everyone talks about it, very few really know how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.

Dan Ariely (free adaptation)

Architecture

HDP - HortonWorks Data Platform

In most of our projects, we have adopted the HortonWorks Data Platform (HDP) as the basic architecture of our big data implementations, complemented by solutions – open and market – to meet the full scope of real-time ingestion, storage, data processing, analytics and business insights from our clients

SiliconLife Scope of Work

Our Big Data Skills

Design, implementation and support of big data corporate projects

Data Science and Modeling Consulting

Data Governance Design and Implementation

Big Data Infrastructure Design, Implementation and Support