Sunday, June 30, 2013
Wednesday, June 26, 2013
Questions for understanding a BO project
Many of the developers always struggle in beginning of a
migration/conversion/consolidation project where they have to understand an existing
SAP Business objects reporting environment and build a new one. They start
collecting the information and there are no set of rules of as-is analysis.
I
worked in several projects where I faced this difficulty and started preparing
a list of question that we need to know about a reporting environment. You can
use this template to start requirement gathering and eventually you will come up
with bigger or smaller list. But you can use it as start point:
Environment details
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Server Name & Connection of all
environments
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TNS entries for all environments
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Universe Details:
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Name & Number of Universe
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Name & Number of star Schemas
with confirmed Dimensions
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Name & Number of tables
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Name & Number of Aliases and
Contexts
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Name & Number of classes with
some subclasses
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Name & Number of objects
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Name & Number of customized
hierarchies
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Name & Number of conditional
objects with time conditions
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Name & Number of default
hierarchies
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Name & Number of aggregate
navigations
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Name & Number of Linked
universe
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Security structure
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Security groups
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Manage access restriction mapping
(groups and security levels) if any.
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Universe connection name for each
environment
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Reporting details:
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Name & Number of Reports
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Name and Number of Linked reports
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Reports with multiple data provider
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Number of report level objects
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Customization of the reports(Means
if there any standard template for the reports)
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If there any specific alerter for
all the reports
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Number of Tabbed reports
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Scheduling time and scheduling
process.
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Multilingual Support information
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Prompts used in reports
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CMC details:
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Access levels of the
system(Security analysis)
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Number of users/groups
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Any customization of Info view is
there..
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Load Balancing system
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Third party software used
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Integration system with the Active
Directory of company with BO
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Documents needed
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Data Model
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Process flows
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Functional specification
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Operation manual
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A single document which track all
objects of all reports available
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Coformed dimension
Conform dimension
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What
is conformed dimension?
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A
Conformed Dimension is any type of dimension that has a single meaning or
value across a data warehouse. Literally word “conform” means ‘to follow
rules and guidelines’. Taking that
a conformed dimension is a dimension which follows the same rule and
guidelines across the data warehouse.
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Example:
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Time
dimension is one of the best examples that fit with Conformed dimension.
In
a fact table if a key ‘20130605’ pass the staging area it should have column
for below information
Year,
Month, day, Quarter, Calender_week
This
dimension table is conformed for all the business area which is using the
data warehouse.
Another
example is a Dealer details in in Automotive industry. Dealer information is one
of the central dimensions for all the sales, after sales, finance, warranty.
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Why
conformed dimension is important?
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Conformed
dimension is best fit for the centralized system. Now a day’s large companies
are centralizing the data which are spread across the organization in
different warehouse application.
Used
dimension in different application may have same or slightly different data.
That creates lots of redundancy and unnecessary usage of resource.
Conformed
dimension proposed by Kimball is to analyze and finalize the dimension which
can be reuse in different application and can be referenced in several
disconnected mart.
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Which
factors is holding back and how to overcome this?
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To
confirm the conform dimension a major collaborative effort is needed across
the organization stakeholders to business analyst and data modeler.
All
potential dimensions which can be conformed dimension may have some
difference in attribute and stakeholders needs to compromise or change the
process for the sake of modeling.
This
happens rare.
Kimball
suggested a way that you don’t need to do conformed dimension in first place.
You don’t have to agree with all the attributes. At a minimum, you should
identify a subset of attributes that have significance across the enterprise.
These commonly-referenced descriptive characteristics will become the starter
set of conformed attributes.
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Who
needs to be involved to confirm a conformed dimension?
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Practically
conformed dimension cannot be done enterprise wide at beginning. You need to
start with the two major applications which is similar in nature. Then
identify commonly referenced dimensions which in future may convert to
conformed dimension.
·
To confirm a conform dimension you need:
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Data Modeler
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Data Architect
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Business Analyst
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Business Owners and stakeholders from each of
the application.
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Business SMEs who have deep knowledge in all the
application.
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Tuesday, June 4, 2013
What is Business Intelligence(BI)?
What
is Business Intelligence?
Business Intelligence was defined by is creator
Hans Peter Luhn an IBM researcher as:
“The ability to apprehend the interrelationship of presented facts in such a way as to guide action towards desired goal.”
“The ability to apprehend the interrelationship of presented facts in such a way as to guide action towards desired goal.”
The sentence was carefully crafted and designed to
define an enormous details in single line. That was 1958 and BI came a long way
and grab the market in next millennium with help of relational database.
We normally start the discussion of BI from Data
Warehouse. Loves to use lots of terms and speak about the fact and dimension.
But unfortunately we never dig into the basic plus and minus sign which makes
the algebra correct.
Let’s
think this way that why the definition needs to wait for more than 30 years to
come into practical life. This is only because a theory cannot work else the
tools are invented to implemented that. The definition got its buddy when the
relational database word was coined by Dr. E.F. Codd. Relational software (now
Oracle Corporation) gives the concept a visual interpretation. The concept and
the tools are fuelled by addition of the letter “I” with Oracle 8 which revolutionizes the way of thinking to keep
the data. Dot com boom did the last finish and we are now enjoying the beauty of
business Intelligence everywhere.
It was easy to tell the story of how a
revolutionary concept evolves and progressed to its absolute form. But still
there is no definition which can accumulate all the parts of Business
Intelligence in a single sentence or a paragraph. As everyone tried to define
it and end up with a definition of its limbs. Better not to define it rather
analyze the holistic view and purpose of Business Intelligence.
Business
and Intelligence
Information Technology always funded by large
companies who wants to keep their data in a retrievable manner. From where the
data come and where the data goes is the main objective of Information
Technology.
Business
or so called industry always struggle to keep organize data and organize
related data retrieval. To run an automotive business they don’t need a excel
sheet but need a hammer. But which size of hammer they need to flatten a piece
of steal should be documented somewhere or a person is needed to remember all
these things which are totally vague.
Now
hammer can be of different size and shape different weight and thrust. And
alone a hammer cannot curve out a body of a car from a sheet metal. You need
chisel, anvil. These also have own measurement. Someone needs to understand the
match and implement in the industry.
As
complex machinery started to invent, keeping thousands of information about
tools are generated. Utilization of those tools with matching different
specification leads to a major confusion. Slowly all observation became data in
a spreadsheet for a technician or a field engineer.
Now
it needs to be matched with different part of a factory – Inventory, where a
technician put its demand and the Inventory manager matches with supply. The
calculation of transaction goes to finance and finance calculates the profit
and loss.
To
hold this dissimilar gigantic data with a backbone of money flow is to be
tracked somewhere. It may be a spreadsheet; it may be a database or may be a
relational database. But how a person from management comes to know that why
factory A is not creating as much car as factory B?
Is
it the hammer that matter? May be, may not be. It may be the employees working
there are depressed and slow down the production because of their low wages. It
may be the assembly line don’t have good amount of inventory and the line stops
frequently. It may be the suppliers are delaying supplying their small parts.
Whatever
it is, business needs to know. They need to understand the root cause. And have
to take decision over Factory A and their employee.
They
have to do it intelligently because the decision makers are accountable to
every person falls under an organization hierarchy, sometimes outsiders
(shareholders). Their decision needs to be supported by a set of data which is
accurate and immediate but based on a statistics over a big set of data which
was gathered over a period of time.
This
intelligence is provided by Information Technology with high volume of data in
all levels of granularity. The power of analysis with the online day to day
data with comparison to historical information slicing and dicing by taking key
performance indicator parameters results a solid reason for all the decisions
company make.
In
a line Business Intelligence is set of theories and concepts which understand
business completely, focus on a subject area, identify the problem area and
provide an intelligence supported by a pure analytical dataset which results to
a decision taken for the good of an organization.
Who needs this and who can afford this?
Any industry can use this as a tool to take
decision. It may be small or may be a major enterprise. But the cost and
expenditure is major as to implement a BI solution you need at least
- A Data warehouse to keep your historical data which will be used for data analysis.
- A data mart which you will use for reporting
- An ETL ( Extraction Transformation Load) tool to load the data in data warehouse
- A reporting tool to see the result data
And all are not very simple to implement and easy
to use. So you need many specialized person to build this environment. As
result a big enterprise which has a large scale of data and need an robust
analytical system can afford this.
Components
of BI
Business Intelligence is a concept and not a tool
to be composed by components. But as it is a common terminology which is used
everywhere that which all can be together call as Component of BI which
actually generates intelligence for business.
My definition of BI components holds the below
values:
Let’s not go deep into as these will be part of
the later article.
Tools
used for BI
Business Intelligence is a tool driven system and
the tools which are generically in use for creating in BI development are all
specialized in particular field.
Though we can find many BI tools in Google
specifically used in BI project but I feel that BI needs almost every tool
which IT world offers. The key to choose your tool is business requirement. We
missed everywhere that requirement gathering in proper manner also need some
tools which efficiently track the requirement and asking for solution.
Let me consolidate my past projects used tool
where you might find some tools which are normally ignored while creating cost
estimation. But those also should have some credit for success of BI.
Requirement Gathering and
documenting Tool
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Requirement
gathering and analysis is the main factor for success of BI project. All the
information gathered need to be documented properly and store in some
document management system which can be searched and retrieve properly and
promptly in time of validation and verification of business rules
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·
Microsoft one notes to take instant note and save.
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Microsoft Visio to create graphical representation of understanding
·
Business Analyst tool to keep the gathered data and create a system
workflow.
·
Microsoft SharePoint to create the data repository
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Screen grabber tool to create snapshot.
·
Audio or video grabbing tool to capture meeting (if organization permit)
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Data Modeling tool
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After gathering the
requirement data need to be modeled properly either following top down
approach or bottom approach.
Data modeling tools
used to create a conceptual model and then convert into a relation model.
Tools are now pretty powerful to create the database from the relational
model diagram.
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SYBASE Power Designer
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RDBMS for Data Warehousing
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Data Warehouse and
Data marts are the concepts which are nothing but a set of table in a
database. To hold that properly modeled data warehouse or DataMart a RDMS is
in need which can process a major set of data and a decent throughput from
query.
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Oracle, DB2, SQL
SERVER
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ETL tool for Data loading
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Extraction
Transformation and load is the mechanism to load data from heterogeneous
sources and formats. This specially designed BI tool take cares all the major
business rules which need to be implemented in database level.
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Informatica,
Datastage
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Reporting tool for showing reports
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Reporting tools are
for end user who will see the clean and summarized data by different criteria
or parameter. A reporting tool is consist of a semantics layer which holds
the business rules which need to implemented in reporting side.
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Business Objects,
Cognos
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Dash boarding tool for showing
dashboard
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Dashboard is also a
reporting environment which provides highly summarized data for KPIs of an
industry.
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Qlikview, Xcelcius,
Crystal report
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Portal development tool
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Some time it is
needed that the application or reporting may not be used directly from the
link but from a different company portal. Sometime the portal is present or
sometime you need to build that.
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Java, .net
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Office package
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Office package is
all along the most important tool in BI. Still there are employees who want
to run the whole company using Excel. Users also love to see the report in
pdf , xls, doc format. So integration with office package is most important
thing in BI reporting
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Microsoft Office,
Open office, Adobe PDF
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Let’s end this article with famous definition of
Data Warehouse by Bill Inmon,
A
data warehouse is a subject-oriented, integrated, time-variant and non-volatile
collection of data in support of management's decision making process.
This is what a BI generally does. It takes a time
span of data over a particular subject area and doing a statistical measure it
provides a data driven support which leads a management to take fearless
decision.
We will discuss this more in other article.
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