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THE BIG DATA ECOSYSTEM AND YOU !. BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:. Social Media and Consumer Sentiment. External Users. Backoffice (ERP). Internal Users. Statistics. Transactional Applications. Unstructured Data. ETL. Business Intelligence. Transactional Data ( OLTP).

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slide2
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Social Media and

Consumer Sentiment

External

Users

Backoffice

(ERP)

Internal Users

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

Data Warehouse

slide3
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Social Media and

Consumer Sentiment

  • Transactional Data – Source Systems and/or Point of Sale
    • Vary Greatly from Company to company
    • EX: Insurance Policy and Claims Systems, Brokerage Trade Systems, Academic Enrollment Systems, Enery Smart Grids, Hospital Patient Management Systems, etc, etc…..

External

Users

Backoffice

(ERP)

Internal Users

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

  • ERP Data – Operational Management, Planning and Feedback
    • EX: Supply Chain, Finance & Accounting, Inventory Management, HR, CRM, etc, etc...

Data Warehouse

slide4
Big Data Decision Point! – Data Mart or EDW

P

ETL, Replication, Data Quality

Key Drivers:

  • What is the Size of your Source Data?
  • Should Big Data sit inside or Outside of your EDW?
  • Normalize or Denormalize?
  • Integrated Reporting or Isolated Reporting?

Enterprise Data Warehouse

Bulk & Trickle Loads

SQL, ODBC,

JDBC

ETL, Replication, Data Quality

App./Reporting front-end

BI or Reporting Interface

slide5
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Social Media and

Consumer Sentiment

  • Moving data from one system to another and getting it right is often the most frustrating and time consuming piece of the BI Ecosystem puzzle
  • Quality - Time - $$$ (is good enough… good enough?)

ETL – Extraction, Transformation, Loading

Or

ELT – Extraction, Loading, Transformation

External

Users

Backoffice

(ERP)

Internal Users

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

Data Warehouse

slide6
Big Data Decision Point! – ETL, ELT or Data Virtualization?

Key Drivers:

  • What is the Quality of your Source Data?
  • How complex is the model?
  • Can the database handle ELT batch rework in time?
  • Do you have the right tools (Informatica, CompositeSW)?
  • Can you live with the maintenance overhead, performace?
slide7
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Social Media and

Consumer Sentiment

Data Warehouse(s?)

Central Storage Tank for most the company’s most critical data

True success requires Executive Evangelism

The ecosystem lives or dies based on the performance of your data warehouse!

External

Users

Backoffice

(ERP)

Internal Users

  • Often very difficult to ROI: “Are your users satisfied with your company’s BI delivery?” - Gartner

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

Data Warehouse

slide8
Old School Tech (Row Store) or

New School Tech (Columnar, NoSQL)?

AAPL

AAPL

BBY

BBY

AAPL NYASE NYAASE NYSE NYASE NGGYSE NYGGGSE NYSE NYSENYSE143.74NYSE NYSENYSE5/05/09

Key Drivers:

  • Can your database handle your data volumes?
  • Does the cost of performance tuning justify status quo?
  • Real-time or batch?
  • Commodity MPP or Big Iron?
  • Are you monetizing your data or heating your data center?
slide9
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Social Media and

Consumer Sentiment

Business Intelligence and Advanced Analytics

Is your corporate culture one that views Business Intelligence output as a key driver to your company’s success?

Can analysts use BI output to make positive, effective, fact-based decisions?

External

Users

Backoffice

(ERP)

Internal Users

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

Data Warehouse

slide10
In-Database Analytics or Application Based Analytics?

Key Drivers:

  • Performance – Cubes or Relational?
  • Are you living in a canned report or ad-hoc world?
  • Does your business have highly advanced, specialized analytics needs?
  • Do your data mining users require the aid of an analytics GUI?
slide11
BIG DATA ECOSYSTEM OVERVIEW DIAGRAM:

Unstructured Data:

The final piece of the big-data puzzle?

Is there data floating around the you need to understand but can’t figure out how to analyze?

Do you know what’s happening on your company’s network? How consumers feel about your product? If your call centers are actually helping your business?

Social Media and

Consumer Sentiment

Web logs / Clickstream

Social Media

Call Center

Consumer Sentiment

Lobs, Blobs, and Clobs

External

Users

Backoffice

(ERP)

Internal Users

Statistics

Transactional

Applications

Unstructured Data

ETL

Business

Intelligence

Transactional Data (OLTP)

Data Warehouse

slide12

Hadoop / Vertica: ETL

Hadoop or not to Hadoop?

Key Drivers:

  • Is it critical you understand your company’s messiest data?
  • Do you have the skills and know-how?
    • HDFS vsMapReduce
  • Could you take action on the information if you had it?
    • Exposing MapReduce results through BI or EDW
  • Are there alternatives to Hadoop?

Computer Cluster

Computer Cluster

Data

data datadatadatada

data datadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

data datadatadatadatadata

DFS Block 1

DFS Block 1

DFS Block 1

DFS Block 1

Map

Map

DFS Block 1

DFS Block 1

DFS Block 2

DFS Block 2

Map

Map

Reduce

Reduce

Hadoop / Vertica: Advanced Analytics

DFS Block 2

DFS Block 2

DFS Block 2

DFS Block 2

Map

Map

DFS Block 3

DFS Block 3

DFS Block 3

DFS Block 3

slide13
Big Data Trends - Data Governance:
  • Data About Your Data
  • Do you really understand your data? Do your users?
  • How many versions of the truth are there?
  • Does your organization have the commitment to build adhere to standards?
slide14
Big Data Trends - Cloud:
  • You *MAY* put your data in the Cloud, but DON’T put your Head there!
  • Public cloud vs. Private Cloud vs. SaaS – What’s best for you?
  • Is it secure? Is it disaster-proof?
  • Does is perform?
  • Is it cost effective?
slide15
Big Data Trends – Mobile:
  • If you’re not delivering Mobile BI to your user and customers, you’ve fallen behind.
  • Tools are making Mobile Delivery easier every day.
  • Your customers expect it. Your internal users *should* expect it.
  • Do you have a Mobile Data Security Strategy?
slide16
Advice for Survival in the Big-Data world:
  • BE PROACTIVE IN TRANSFORMING YOUR BUSINESS!
  • STAY ON TOP OF NEW TECHNOLOGIES!
  • PARTNER WITH THE BUSINESS!
  • BE AWARE OF THE BIG DATA TECHNOLOGY YOU INTERACT WITH EVERY DAY, AND APPLY IT TO YOUR BUSINESS!