• Like
Introduction  to Big Data
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

Introduction to Big Data

  • 223 views
Published

A short presentation to introduce the idea of big data in IT, its suporting trends and possible tools.

A short presentation to introduce the idea of big data in IT, its suporting trends and possible tools.

Published in Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
223
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
6
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Big Data ● What is it ? ● What trends in IT support it ? ● Some examples ● What tools are used ? ● The future ?
  • 2. Big Data – What is it ? ● Very large data set volumes ● Very long / unacceptable processing times ● Very large data velocity ( inputs / outputs ) ● Very large varieties of data ● High level of complexity
  • 3. Big Data – Supporting Trends ● Moore's Law An observation that the number of transistors on integrated circuits doubles every two years.
  • 4. Big Data – Supporting Trends ● Kryder's Law The density of storage is increasing and the cost decreasing at a rate faster than Moore's Law.
  • 5. Big Data – Supporting Trends ● Butter's Law Relates to network capacity and states that the cost of sending data over an optical network halves every nine months.
  • 6. Big Data – Supporting Trends ● Parallel Processing Task parallelism, breaking the task down into its constituent parts and processing them simultaneously.
  • 7. Big Data – Examples ● NASA Climate Simulation 32 petabytes ● The Large Hadron Collider 25 petabytes annually, 200 petabytes after replication ● Wall mart 2.5 petabytes per hour
  • 8. Big Data – Tools ● Hadoop Hadoop is often used at the server level to organise the cluster along with a NoSQL database for data storage. ● NoSQL Databases ( non sql ) that use looser consistency models than relational databases. Performance gains via simplification using key value stores. ● MPP Massively parallel processing and analytics databases. Fast for data aggregation but slow for data loading.
  • 9. Big Data – The Future ● Data sets will continue to grow ● Storage unit costs will continue to decrease ● Processing costs will decrease ● Network capacity will continue to grow ● Data growth may exceed processing capacity
  • 10. Contact Us ● Feel free to contact us at – www.semtech-solutions.co.nz – info@semtech-solutions.co.nz ● We offer IT project consultancy ● We are happy to hear about your problems ● You can just pay for those hours that you need ● To solve your problems