CODEWITHSUNDEEP
hadoopanalyticsbigdatabusiness-intelligence
SharpCoder
SharpCoder

Reputation: 19193

Big data case study or use case example

I have read lot of blogs\article on how different type of industries are using Big Data Analytic. But most of these article fails to mention

  1. What kinda data these companies used. What was the size of the data
  2. What kinda of tools technologies they used to process the data
  3. What was the problem they were facing and how the insight they got the data helped them to resolve the issue.
  4. How they selected the tool\technology to suit their need.
  5. What kinda pattern they identified from the data & what kind of patterns they were looking from the data.

I wonder if someone can provide me answer to all these questions or a link which at-least answer some of the the questions.

It would be great if someone share how finance industry is making use of Big Data Analytic.

Upvotes: 2

Views: 675

Answers (2)

Hamideh
Hamideh

Reputation: 697

I think getting what you want is a difficult job getting data little by little from different resources. just make sure to visit these links:

a bunch of free reports. I am studying the list right now. http://www.oreilly.com/data/free/

and the famous McKinsey Report: http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights%20and%20pubs/MGI/Research/Technology%20and%20Innovation/Big%20Data/MGI_big_data_full_report.ashx

Upvotes: 0

Junayy
Junayy

Reputation: 1150

Your question is very large but I will try to answer with my own experience

1 - What kinda data these companies used ?

One of the strength of Hadoop is that you can use a very large origin for your data. It can be .csv / .txt files, json, mysql, photos, videos ...
It can contains data about marketing, social network, server logs ...

What was the size of the data ?

There is no rules about that. It can start from 50 - 60 Go to 1Po. Depends of the data and the company.

2 - What kinda of tools technologies they used to process the data

No rules about that. Depends of the needs. To organize and process data they use Hadoop with Hive and Pig. To query data, they want some short response time so they use NoSQL / in-memory database with a shorter dataset (refined by Hadoop). In some cases, company use ETL like Talend in order to go faster.

3 - What was the problem they were facing and how the insight they got the data helped them to resolve the issue.

The main issue for company is the growth of their data. At a moment, the data are too big and it is impossible to process with traditional tools like Mysql or others. So they start to use Hadoop for example.

4 - How they selected the tool\technology to suit their need.

I think it's an internal problematic. Company choose their tools because of the price of the licence, their own skills, their finals needs ...

5 - What kinda pattern they identified from the data & what kind of patterns they were looking from the data.

I don't really understand this question

Hope it will help you.

Upvotes: 1

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