What is an OLAP ? Why is it so simple and so intriguing ?

1. O.L.A.P.
(Online Analytical Processing)
By creating doubt you may find certainties.
Certainties do not create enterprise. Doubt and questions do.
Dedicated to Dr. Ing. Andrea Fraschetti, my uncle, a Ferrari man who personally circuit tested,
because he had doubts, a racing car he designed and died doing so
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Release 13 August 2012

2. Thank you to the following reviewers of this presentation
Mr. Dean Tallam – Senior Manager of SciFinance, Inc
"...SciFinance takes complex mathematical models and translates them into something a
computer can solve, allowing banks to flexibly change pricing models as they introduce new
products." Newsweek International
Ing. Filippo Heilpern - Consultant in BD & International, Corporate Executive
Dr. Ignazio Palau – Consultant in BD & International, Corporate Executive
My son Lorenzo
Some, among others, sources
Introduction to OLAP - Slice, Dice and Drill! - Hari Mailvaganam
BUSINESS INTELLIGENCE for DUMMIES – Swain Scheps (2008)
Data Warehousing Part 1 : OLAP and OLTP – Mike Brunt
OLAP Workshop : Basic overview of OLAP Concepts – Keith Laker
MS SQL Server 7.0 OLAP Services – Microsoft Inc.
http://whatis.techtarget.com
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3. Your multidimensional business query
Given what are my needs, where can I find in 3 areas/regions (France, Europe,
South America) and from 2 countries (India and China) the offers that reflect the
needs of the industry whom I can fulfill with my acquired educational skills ?
This personal question describes both the data that you need to examine
and the way you need the data structured
Some of the questions contained in the above query :
 What is my product ? (“…my needs…”)
 Where can I sell it ? (“…3 areas/regions…and from 2 countries..”)
 Who wants to buy it (“… the offers…”)
 How much ? (you are too green, forget about it for the moment….)
YOUR ANSWER TO THIS QUERY ?
FOOD FOR YOUR THOUGHTS
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4. OLAP
is
 working with data & information - in business terms - without needing to
understand the underlying storage mechanism
as well as
 having the ability of intelligently and transparently working with the
different types of business rules that exist within any organisation and
sustain/support them
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5. It has also been defined as
Fast Analysis of Shared Multidimensional Information
Fast
Delivers information to the user at a fairly constant rate.
Most queries should be delivered to the user in five seconds or less.
Analysis
Performs basic numerical and statistical analysis of the data, predefined by an
application developer or defined ad hoc by the user.
Shared
Implements the security requirements necessary for sharing potentially confidential
data across a large user population.
Multidimensional
Not bi-dimensional, not tri-dimensional, multidimensional
Information
Accesses all the data and information necessary and relevant for the application,
wherever it may reside and not limited by volume 5

6. Keep well embedded in your mind the two terms
SHARED
MULTIDIMENTIONAL
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7. Multidimentional Data Model
DIMENSIONS
descriptive cathegories
MEASURES
quantitative
values
SHARED
MULTIDIMENTIONAL
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8. O.L.A.P is an approach that may quickly provide answers to analytical
queries that are multi-dimensional in nature.
Think at the queries you have about your future :
What do I need ?
What do I want ?
What does the market offer ?
What is my offer to the market ?
What are the skills that I can bring to the market ?
How can I match these with the offer ?
How do I find the sources of the offer ?
When and how do we “tango”, the offer and me ?
The typical applications of OLAP are in business reporting for sales,
marketing, management reporting, business process management (BPM),
budgeting and forecasting, financial reporting, etc.
In your case finding a challenge which you will love !
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9. It is used extensively by Intelligence Services and Intelligence Agencies (a
prime example, the E.C.H.E.L.O.N evesdropping program from the N.S.A. in
the US, that along with the F.B.I., just detected massive intrusions in Obama’s
and McCain’s campaigns data bases)
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10. Databases configured for OLAP employ a multidimensional data
model, allowing for complex analytical and ad-hoc queries with a rapid
execution time.
They borrow aspects of navigational databases and hierarchical databases
that are speedier than their relational kin (proche).
The output of an OLAP query is typically displayed in a matrix (or pivot)
format.
The dimensions form the rows and columns of the matrix; the
measures, the values.
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11. OLAP Data Model
In an OLAP data model, information is conceptually viewed as cubes,which
consist of descriptive categories (dimensions) and quantitative values
(measures).
The multidimensional data model makes it simple for users to formulate
complex queries, arrange data on a report, switch from summary to detail data,
and filter or slice data into meaningful subsets .
Cubes is an easy expression to describe a form.
In the real business world OLAP can be multi-dimentional & multifaceted with
5,6,7,…x… dimensions and measures
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12. To simplify
Dimension is What Time
Geography
Product
Channel
Organization
Scenario (budget or actual)
Measure is How Much € Sales
Unit Sales
Inventory
Head counts
Income
Expenses
Profits/Losses
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13. Multidimentional Data Model
MEASURES :
quantitative
DIMENSIONS : values
descriptive cathegories
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14. OLAP environment is centred around use of the term “business
intelligence” where the emphasis is on
“online” or active access
“dynamic”
“analytical” in terms of the reports that are generated.
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15. online WHAT ?
dynamic WHAT ?
analytical WHAT ?
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16. Online
a. Live access to data rather than static reporting.
b. Analytic queries are submitted against the database in real time, and
the results are returned in real time.
Analytical processing
i. Easily navigate multidimensional data to perform unpredictable ad hoc
queries and display the results in a variety of different layouts
ii. Transparently manage business rules across dimensions and cubes
iii. “Drill through” levels of detail to uncover significant aspects of data
iv. Rapidly and efficiently obtain the results of sophisticated data
calculation and selection across multiple dimensions of data
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17. A few definitions
A metadata repository is a database of data about data (metadata).
The purpose of the metadata repository is to provide a consistent and
reliable means of access to data. The repository itself may be stored in a
physical location or may be a virtual database, in which metadata is
drawn from separate sources. Metadata may include information about
how to access specific data, or more detail about it, among a myriad of
possibilities.
A data warehouse is an Enterprise reporting solution. It will typically
hold all historical data for the company for all time.
A datamart is a smaller version of the data warehouse. It's going to hold
a year or two's worth of information, and may not hold all the tables in
the data warehouse.
While the data warehouse is for the enterprise, a datamart is typically
for a department’s use.
Source http://whatis.techtarget.com 17

18. Output
Analytical processing
Online
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19. One standard transactional report or query will ask the following question :
When was order number 84305 shipped?
This simple, down-to-earth, two-dimensional query reflects basic
mechanics/data of doing business.
a. Date of shipment
b. Order Number
It involves simple data selection and little or no calculation processing.
It can be answered directly from the transactional system without any impact
other operations.
No organisation can survive without this basic level of information.
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20. OLAP systems – on the other hand - allow an organization’s to answer a
much broader multi-dimentional range of business queries about the data they
are collecting in their transactional systems:
i. How do same quarter sales for our top 10 most profitable
products across EMEA Region for this quarter compare with sales
a year ago?
ii. What are the differences in the product-sales mix between
Regions Scandinavia, North, Central and South Europe , in
context to the global European sales mix?
iii. What are our forecast units, unit price per service, unit cost per
product, sales, cost trends, and profit for the next 12 months?
iv. In what ways does the mix vary by salesperson, and what is the
relative performance of our salespeople?
v. What are , year to date, the products making up to 40% of our
gross profit for each Region over the period 2006 to 2008?
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21. Two illustrations of OLAP
scenarios/architecture that can
allow broad multi-dimentional
business queries
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22. Figure 1. Data Model for OLTP
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23. 23

24. The main differences between a simple two dimentional transactional query
and broader multi-dimentional queries are :
i. the fact that
the latter are
much more
analytical and
quite
complex,
ii. that the
answer to one
question
often leads
immediately
to another
question as
the user
follows a
train of
thought in
addressing 24
a
business

25. OLAP is designed to make it easy for end users to ask broader multi-dimentional
range of analytical queries and enhance its day-to-day use without requiring:
Assistance from the IT department
Programming skills
Technical knowledge about the organization of the database
The results of queries also need to be rapid so that the analyst’s train of thought
is not interrupted and the value of the analysis is not diminished.
Time and reaction time is of essence in any business scenario. Information is old
the minute it is generated.
If it is generated late it could be obsolete.
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26. A typical multidimensional business query
For each region of France, what was the percentage change in revenue for our top
15% products, over a rolling three-month period this year starting March compared
to the same period last year?
This rather simple business question describes both the data that the user wants to
examine and they way he wants the data structured (i.e.: structural form of that data).
Business users typically want to answer questions that include terms such as
what, where, who, when and, above all, how much !
You find the following essential questions contained in the above query :
 What products are selling best? (“…top 15%…”)
 Where are they selling? (“…each region France…”)
 When have they performed the best? (“…over a rolling period….starting March…”)
 How much ? (“…percentage change in revenue…”)
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27. Your multidimensional business query
Given what are my needs, where can I can find in 3 areas/regions (France, Europe,
South America) and from 2 countries (India and China) the offers that reflect the
needs of the industry whom I can fulfill with my acquired educational skills ?
This personal question describes both the data that you need to examine
and the way you need the data structured
Some of the questions contained in the above query :
 What is my product ? (“…my needs…”)
 Where can I sell it ? (“…3 areas/regions…and from 2 countries..”)
 Who wants to buy them (“… the offers…”)
 How much ? (you are too green, forget about it for the moment….)
YOUR ANSWER ????? FOOD FOR YOUR THOUGHTS
GOOD HUNT WOLF PACK !
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