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Data integration my_experience

Date post: 30-Jun-2015
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Best Practices in Data Integration
21
MY STORY Designed By Arvind Murali
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Page 1: Data integration my_experience

MY STORY

Designed ByArvind Murali

Page 2: Data integration my_experience

MY NAME IS ARVIND MURALI

I LIVE IN APPLE VALLEY, MN

I AM A DATA INTEGRATION EXPERT

I WORK FOR HIGHPOINT SOLUTIONS

HELLO

Page 3: Data integration my_experience

ABOUT HIGHPOINT

Page 4: Data integration my_experience

My Evolution in Data Integration

Page 5: Data integration my_experience

Started as a Datawarehouse Analyst/Designer

Sorting through 100’s of entities To analyze and report data in excel

My Humble Beginning

Page 6: Data integration my_experience

Time to move on to bigger and better things!! Marriage.

&

DATA INTEGRATION CONSULTING

FFWD Three Years

Page 7: Data integration my_experience

Moving ON to even better things. My Son!!

&

INTEGRATIONS SOLUTIONS LEAD (Why we are doing what we are

doing?)

FFWD Two More Years and ever since…

Page 8: Data integration my_experience

CHALLENGES

Page 9: Data integration my_experience

Storing all irrelevant information only to find out increased Storage and performance slowness.STICK TO REQUIREMENTS. DO NOT OVERDO.

Challenge 1 – Relevance

Page 10: Data integration my_experience

Operational Databases

Data Integration

Hub

Ontology

Rules Repository

CRM Social Media

Synchronizing huge quantities and formats of data with internal and external systems.

Challenge 2 – Heterogeneous Data

Page 11: Data integration my_experience

Data Quality & Data Audit are 2 of the most critical components of any data integration effort. Developers and Users should work together to determine the quality control metrics and

measures.

Challenge 3 – Data Quality

What is Data Quality?

Page 12: Data integration my_experience

Because of the involvement of hardware and software to accomplish data integration, it is common to see some unexpected costs in the process.

• Labor costs for initial planning, evaluation, programming and additional data acquisition.• Software and hardware purchases.• Unanticipated technology changes/advances.• Both labor and the direct costs of data storage and maintenance.

Challenge 4 – Unanticipated Cost

Page 13: Data integration my_experience

Data Integration Lead, Data Stewards, Analysts, Designers, and Data Managers are a MUST with practice experience in data management arena. In addition, setting incremental goal helps

understand, deliver, and monetize mission.

Challenge 5 – Expertise

Page 14: Data integration my_experience

BEST PRACTICES

Page 15: Data integration my_experience

Understand and Clarify the end goal (BIG PICTURE) with your Stakeholders.

Lesson 1 – End Goal

Page 16: Data integration my_experience

Gather Requirements and Specifications Thoroughly and as much detailed as possible.

Lesson 2 -- Requirements

Page 17: Data integration my_experience

Understand and Design Industry and Organizational Standards customized to process. ONCE DEFINED, STICK TO THOSE STANDARDS.

Lesson 3 –Standards

Page 18: Data integration my_experience

A thorough analysis of characteristics and usage of data to mitigate bad and heterogeneous data challenges.

Lesson 4 – Data Analysis

Page 19: Data integration my_experience

Go GAGA over testing. Most critical phase of integration.

Lesson 5 – Testing

Page 20: Data integration my_experience

THE PROCESS!!

Page 21: Data integration my_experience

REFERENCES

Information Management MagazineDilbert Cartoons

The Datawarehouse Institute (TDWI)Cartoons for Data

Data Integration Slideshares


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