|
|
Executive Summary
The Big Issue:
Customer Relationship Management (CRM), Big Data , Data Centers, Business Intelligence,
Analytics, Security and Data Streaming are the common buzzwords these days. The real
challenge is what to make of the growing data and how to use it to the business
advantage. All the Big Data players including Amazon Web Services (AWS) claim to have
the answers for business to be in the cloud. Sadly, almost all CEOs and stakeholders
buy into these Big Data players' claims and the best example is the big failure called
Hadoop. Looking at how a pod of whales may strand themselves to death for following
their weak whale leader that no longer has the energy to stay afloat. CEOs need to
check which pod they belong to and when the stranding would start.
Our Simple Answer:
CRM as a tool or an engine is not fully utilized, despite what you see on web
and mobile with all ads showing up with your recent purchases or search. The
ads shown or displayed are kind of clumsy and lack intelligence. CRM as an
engine should be able to look at the client's recently purchases and search. It
should also parse or evaluate every customer who has similar income, habits,
trends, education, live in similar neighborhood, etc and all are guided by the
dynamic business rules. These business rules govern the outcome of the CRM
analysis. This means the client's personal data and maybe ten million customers
data must be evaluated-processed on the run and customized web or mobile pages
would be generated on the spot to guide the client on his next purchases.
What we just described is a real-time-dynamic CRM analysis that uses Big data. It
is also guided by the dynamic business rules. The amount of data processed for any
CRM system would be take a long time and not to mention, there are new data added
to the client data, with every visit, purchases, searches or events associated
with the client.
Our CRM Metadata is an answer to such monumental task. Our Key ingredient is building
Bit (zero and ones), Indexes, hashing matrixes and a limited number of table to turn
data into numbers for intelligent-faster-economical processes with dynamic business
rules guidance. For example, we can store someone's credit rating and income in
one byte (8 bits) mapping as follows:
|
|
Credit Rating
|
Index
|
Value
|
|
|
Very poor
|
000
|
Zero
|
|
|
Poor
|
001
|
One
|
|
|
Fair
|
010
|
Two
|
|
|
Good
|
011
|
Three
|
|
|
Excellent
|
100
|
Four
|
The remaining 5 bits can store income where each bit can be a multiple of $10,000 or $20,000:
|
|
Income Range
|
Index
|
Value
|
|
|
$10K-$20K
|
00000
|
Zero
|
|
|
$30K-$40K
|
00001
|
One
|
|
|
$50K-$60K
|
00010
|
Two
|
|
|
. . .
|
. . .
|
. . .
|
|
|
$?K-$?K
|
11111
|
31
|
In conclusion, our CRM Metadata is a sure answer to an intelligent-faster-economical data processing.
|
|
