achieving business value with big data - i

7/29/2019 Achieving Business Value With Big Data - I

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A presentation by

W H Inmon

ACHIEVING BUSINESS VALUE

WITH BIG DATA


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Big Data its everywhere


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Map Reduce Hive

sources of data analytical

processing

budget

compatibility

what the analyst sees today

Cirro Mongopig


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It is one thing to talk about the technology and challenges

of Big Data, but it is another subject when it comes to talking

about getting Business Value out of Big Data


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Big Data TextualDisambiguation

Business

Value

Here is what lies ahead in addressing the topic of

achieving business value out of Big Data

Unstructured data


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Big Data Textual

Disambiguation

Heres what everyone

is talking about

Here is the even bigger hurdle

that no one is talking about


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The reality everything in Big Data is unstructured

texttext

text

texttext

text

texttext

text

text

text

text

text

text

text

texttext

text

text

text

text

text


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texttext

text

texttext

text

texttext

text

text

text

text

text

text

text

text

text

text

text

text

text

text

You can solve all the technical problems of Big Data, but if you

dont also solve the problems of unstructured data, there is no

Business Value


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Big Data

Unstructured Data

All Big Data is unstructured;

Some unstructured data is not Big Data


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and whats so challenging about

raw text?

it is dangerous and potentially

very misleading to try to useraw text as a basis for decisions.

the answer is seven

seven what?seven days?

seven dollars?

seven wonders of the world?

seven seas?

seven dwarfs?

Consider the following confusion..


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Shes hot.

what is being said here?

she is attractive and I want to date her

it is Houston Texas and it is 98 degrees. She is sweating

I just took her temperature and it was 104 degrees..

looking at the words Shes hot tells you nothing

in order to make sense of the text you MUST supply context

and that is true for ALL text

Or consider this confusion..


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But context is not the only problem with text

Log record -

12p98**711>>?mmnaYYt009qqoiy3GGHt

13p99%%899?mmbbaf882qwooi4GGHtf

16p97*&*8772


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But context and interpretation are

not the only problems with text

May 5, 2013

2013/07/2301/13/2014

July 20th of 1945 Standardization of certain common

values is also needed


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Textual

disambiguation

In order to achieve Business Value,

the raw text found in Big Data must pass through

a process known as textual disambiguation


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so how do you do textual disambiguation?

documents

taxonomiesontologies

qualified

vocabulariesdocument

metadata

document sensitive

inference

textual

proximity

acronymresolutions

homographic

resolution

The first step is to contextualize

the raw data


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The problem with contextualization is that

there are many ways to contextualize thetext, all depending on the text


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Interpretation

And what about interpretation?


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Flt 462 DNV to ORD lst bgs CN 235-PO-908

Flight 462 Denver to Chicago lost bags claim number 235-PO-908

Flight 462 Denver to Chicago lost bags claim number 235-PO-908

Flightnumber

City City ActivityOperand Claim number Tone

noneFlight typeUS

Airline agent message

In order to make sense of an airline agent record, it must first be

interpreted, then the interpretation must be contextualized


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May 5, 2013

2013/07/23

01/13/2014

July 20th of 1945

Date - 20130505

Date - 19450720

Date - 20140113

Date - 20130723

Standardization of dates


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Textual

disambiguationStandard dbms

raw

disambiguated Inmon/Krishnan Big Data Architecture

achieving business value with big data - i

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