Big Data Concepts

These days everybody seems to be working with "big data". But what does this mean precisely? What kind of data are we talking about? Whiat infrastructure does it need? And importantly - what does it buy us?

The effective use of data is vital to any enterprise, and the analysis of data to optimise processes and to ensure accurate decisions is not new. But, because of massively increasing data volumes, the increasing diversity of data sources, and the broader availability of data, such analysis demands more from the infrastructure, the software, and the data models. In so far even that it seems like a new framework will be necessary. The traditional, established relational model seems to fall short in describing and guiding the new challenges of "data analysis for business intelligence".

"Big data analytics" is the name of this coordinating framework, in which both old models and techniques (like date warehousing, online analytic processing, Hadoop, cluster analysis, ...) and newer insights (data in motion, emotional text analytics, ...) have found each other. The capability to condense relevant insights from more diverse, larger, and rapidly changing data will help managers and other decision makers to better support their decisions.

This course gives a clear and concise picture of big data and what it represents, providing an overview of the technologies on which Big Data is based, and explaining the frequently heard technological terms that we now need to assimilate.

This course is also available for one-company, on-site presentations and for live presentation over the Internet, via the Virtual Classroom Environment service.

This course is only available for one-company, on-site presentations.

What you will learn

On successful completion of this course you will be able to:

compare NoSQL databases with relational databases
idetify performance issues
explain and use big data analytics
list the principal currently avaiable products.
explain the concepts of big data
understand and use the terminology found in a big data environment
describe big data architecture
identify sources for big data in their own businesses and environments.

Who Should Attend

This course is designed for everybody who wants to learn about big data: IT personnel, people confronted with big data technologies. Also for non (IT) technical collaborators.

Prerequisites

Elementary knowledge of database management systems is an advantage.

Duration

1 day

Fee (per attendee)

P.O.A.

This includes free online 24/7 access to course notes.

Hard copy course notes are available on request from rsmshop@rsm.co.uk

at £50.00 plus carriage per set.

Course Code

BDCA

Introduction to Big Data

Data; databases; data warehouses; and now - big data.

What is Big Data?

Perspective: problem formulation - why big data?; Data centric management; The 4 Vs: volume, variety, velocity, variability; Types of data - examples; Data quality, consistency, and reliability (veracity); Big data architecture: components, technologies: Towards an integrated data architecture.

Overview of New Data Sources

Web statistics ("click streams"); social media; Twitter feeds; Google Maps; sensor data (e.g. surveillance cameras).

Databases

NoSQL databases versus relational databases - types and use; The "divide & conquer" model: Hadoop and MapReduce; Distributing data and analysing it through massively parallel algorithms.

Performance Considerations and Big Data Analytics

Know your data -- or: the role of the data scientist!; How to judge data quality; risk analysis; Use of visualisation tools in order to keep an overview and to estimate the relative importance of the different data sources; Overview of the most often used (open source) products/technologies on the market.