LifeSaver: Differences between UDT and IDT


LifeSaver: Differences between UDT and IDT

Differences between UDT and IDT - universe design tool and the information design tool

The information design tool or IDT is a new modeling tool from SAP for the semantic layer that enables you to play with metadata from relational and OLAP sources, and to create and deploy SAP BusinessObjects universes.

The old Business Objects 3.1 Classic universe features available in Universe Designer have been redeveloped and incorporated in the information design tool.

This post will help you in finding the options in IDT which you must be already very familiar in Universe Designer. Thus enabling you to migrate from BO 3.1 XI to BO 4.0 with no issues.
Start using IDT based on your expertize of Universe Designer.
Universe design > Quick Design Wizard
No similar functionality

Relational universe creation workflow:
1. Click File > New > Project.
2. Click File > New > Relational Connection.
3. Click File > New > Data Foundation.
4. Click File > New > Business Layer.

OLAP universe creation workflow:
1. Click File > New > Project.
2. Click File > New > OLAP Connection.
3. Click File > New > Business Layer.

File > Import
Click File > Retrieve a Published Universe.
File > Export

Universe publishing workflow:
1. From within Local Projects, right-click the Connection (*.cnx) and
click Publish Connection to a Repository.
2. From within Local Projects, right-click the Business Layer (*.blx) and click Publish > To a Repository.

File > Metadata Exchange
No similar functionality

File > Parameters > Definition > Description
From within a Data Foundation (*.dfx), click Properties.
File > Parameters > Definition > Connection

Relational connection workflow:
1. Click File > New > Relational Connection.
OLAP connection workflow:
1. Click File > New > OLAP Connection.

File > Parameters > Summary
From within a Data Foundation (*.dfx), click Properties > Summary.
From within a Business Layer (*.blx), click Properties > Summary.

File > Parameters > Links
No similar functionality

File > Parameters > Strategies
No similar functionality

File > Parameters > Controls
From within a Business Layer (*.blx), click Properties.

File > Parameters > SQL
From within a Data Foundation (*.dfx), click Properties.
From within a Business Layer (*.blx), click Properties.

File > Parameters > Parameter
From within a Data Foundation (*.dfx), click Properties > Parameters.
From within a Business Layer (*.blx), click Properties > Parameters.

File > Print
From within the Local Projects view, right-click a Business Layer (*.blx) and click Print.
From within the Local Projects view, right-click a Data Foundation (*.dfx) and click Print.
From within a Data Foundation (*.dfx), click Print View to Bitmap.

Edit > Undo Action
Click Edit > Undo Action.

Edit > Find/Replace
Click Window > Find/Replace.
From within a Business Layer (*.blx), click Show/Hide Search Panel.
From within a Data Foundation (*.dfx), click Show/Hide Search Panel.

Edit > Hide Item(s)
From within a Business Layer (*.blx), right-click an object and click Change State.

Edit > Object Properties > Definition
From within a Business Layer (*.blx), double-click an object.

Edit > Object Properties > Properties
From within a Business Layer (*.blx), double-click an object and click Advanced.

Edit > Object Properties > Advanced
From within a Business Layer (*.blx), double-click an object and click Advanced.
From within a Business Layer (*.blx), right-click an object and click Change Access Level.

Edit > Object Properties > Keys
From within a Business Layer (*.blx), double-click an object and click Keys.

Edit > Object Properties > Source Information
From within a Business Layer (*.blx), double-click an object and click Source Information.

Edit > Object Format
From within a Business Layer (*.blx), right-click an object and click Edit Display Format.

Edit > Rename Table
From within a Data Foundation (*.dfx), right-click a table and click Edit.

Edit > Edit Derived Table
From within a Data Foundation (*.dfx), right-click a Derived Table and click Edit.

View > Arrange Tables
From within a Data Foundation (*.dfx), click Auto Arrange Tables.

View > Refresh Structure
From within a Data Foundation (*.dfx), click Detect > Refresh Structure.

View > Table Values
From within a Data Foundation (*.dfx), right-click a table and click Show Table Values.

View > Change Table Display
From within a Data Foundation (*.dfx), right-click a table and click Display.

View > Number of Rows in Table
From within a Data Foundation (*.dfx), click Detect > Row Count.

View > Grid Lines/Page Breaks
No similar functionality

View > List Mode
No similar functionality

Insert > Tables
From within a Data Foundation (*.dfx), click Insert > Tables.

Insert > Stored Procedures
No similar functionality

Insert > Derived Table
From within a Data Foundation (*.dfx), click Insert > Derived Table.

Insert > Alias
From within a Data Foundation (*.dfx), click Insert > Alias.

Insert > Join
From within a Data Foundation (*.dfx), click Insert > Join.

Insert > Context
From within a Data Foundation (*.dfx), click Aliases and Contexts > Insert Context.

Insert > Class/Subclass
From within a Business Layer (*.blx), click Insert Item > Folder.

Insert > Object
From within a Business Layer (*.blx), click Insert Item > Dimension.
From within a Business Layer (*.blx), click Insert Item > Measure. From within a Business Layer (*.blx), right-click a dimension and click New > Attribute.

Insert > Condition
From within a Business Layer (*.blx), click Insert Item > Filter.

Insert > Candidate Objects
No similar functionality

Insert > User Objects
No similar functionality

Insert > Universe
No similar functionality

Tools > Connections
From within a Data Foundation (*.dfx), click Connection.
From within a Data Foundation (*.dfx), click Connection > Change Connection.
From within Repository Resources, click Session > Connections.

Tools > Hierarchies
From within a Business Layer (*.blx), click Navigation Paths.

Tools > List of Values
From within a Business Layer (*.blx), click Parameters and Lists of values.
From within a Data Foundation (*.dfx), click Parameters and Lists of values.

Tools > Aggregate Navigation
From within a Business Layer (*.blx), click Actions > Set Aggregate Navigation.

Tools > List of Aliases
From within a Data Foundation (*.dfx), click Aliases and Contexts.

Tools > List of Derived Tables
No similar functionality

Tools > Query Panel
From within a Business Layer (*.blx), click Queries.

Tools > Automated Detection
From within a Data Foundation (*.dfx), click Detect.

Tools > Check Integrity
From within a Business Layer (*.blx), click Check Integrity.
Click Window > Check Integrity Problems.

Tools > Login As
From within the Repository Resources view, click Insert Session.

Tools > Change Password
No similar functionality

Tools > Manage Security
Click Window > Security Editor.

Tools > Options
Click Window > Preferences.

Window > Arrange/Split
From within a Data Foundation (*.dfx), click Insert > View.


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QlikView advantage over query based BI


QlikView advantage over query based BI

Query-based BI tools have been in and around for decades for decision support. Variations of query-based BI software are on the market, Some are flexible and others are high-performance.
But they all share one critical flaw: they are unable to inherently maintain associations among data elements
Query-based tools divorce data from its context. People making complex business decisions don’t always have full access to their supporting data, even when they have access to BI software.
Some data is available only as isolated and discrete queries, without context between one query and the next. This leaves gaps for people trying to make data-driven business decisions.

With query-based tools, creating associations among all available data elements would require a business analyst or IT professional to cram every associated field into a single query, a nearly impossible task.
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The alternative hard coding associations among queries into the application layer is equally daunting.

QlikView is the world’s first associative, in-memory business intelligence platform. QlikView manages associations among data sets at the engine level, not the application level, by storing individual tables in its in-memory associative engine.
Every data point in the analytic dataset is associated with every other data point in the dataset. Datasets can be hundreds of tables with thousands of fields. Unlike traditional query-based BI tools, when the QlikView user selects a data point, no queries are fired.
Instead, all the other fields instantaneously filter and re-aggregate themselves based on the user’s selection. Selections are highlighted in green. Datasets related to the selection are highlighted in white.
Unrelated data is highlighted in gray. This provides a very intuitive, user-friendly way for people to navigate their data on their way to business insight.

Query-based BI tools separate the application layer from the data layer. This leads to long deployments while expensive developers customize the application layer to manage the specific associations required to answer a particular business question.

When the BI application needs to answer a slightly different business question, the application layer must be altered again, which is time-consuming and expensive.
With QlikView, any and all aggregates are recalculated in real time, regardless of the source fields. All associations are stored generically against the entire dataset, ready to answer any business question as it comes up without requiring any customization. The data from all tables is always available in context and ready to answer the next business question.

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LifeSaver: Business Intelligence Projects - Success and Failures


LifeSaver: Business Intelligence Projects - Success and Failures

When we talk about business intelligence, we talk about how a certain project was hugely successful while some did not even walk on its feet. We analysed the situation and found few known-unknown combination of things.

Commonly, companies and CIO offices complain about many stuff during and for a BI implementation. We think the top 3 are:
  1. Data - less or more data, accessible or not-so-accessible data
  2. reports and dashboard that are slow in response and probably not suited for the need
  3. IT specific analytics tools which needs training at technical level
Even with these complaints, BI has been a top implementation priority for many years now. Organizations do recognize the value of data and analytics for decisions and outcomes.
So, there is a big need that the BI initiative does not stop and be a part of failed projects. Question is - how can you ensure this?

Answers is not specific to BI — it is same as any other project. For BI, it is even more difficult because the projects are more difficult to kick off and leap. Plus there are many examples on the list of failed BI projects. So, ensuring BI project's success is not just necessary for companies but also of immediate importance.

I always believed that the business have to drive the initiative for BI projects as they are the best judge of its usage. IT, needless to say, plays big part too. So, it ends up being a balance between the two.

We can come up with some major points as necessity for success of BI project
  1. Start from business and keep business in business intelligence
  2. Independence from IT - self service by business a priority
  3. Data as Good foundation
  4. Tools suitable for organization and people
  5. Train the users and prepare them for independence and change
Along with these, some things needs to be avoided too like AVOID
  1. IT-led - which seems easy but often ends in failure due to lack of business inputs
  2. Too strict or no process
  3. Using governance in everything
  4. Shedding responsibilities if external partners are brought to help
  5. Too much focus on development using tools
  6. Ignoring user training.
Hope this helps to achieve success in BI implementations.

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Data Quality in ETL and BI


Data Quality in ETL and BI - Reasons Impacts Solutions and Operations

The amount of Data that an organization stores and processes in the current time has increased many folds. This has also exposed the associated problems of poor quality of data. If the quality of data is bad then the information created by that data is not useful. Lot of efforts and money is being put in by organizations to improve the quality of data.
The Quality of data refers to the following
  • Accuracy
  • Consistency
  • Integrity
  • Uniqueness
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Reasons for data quality issues:
  • Inaccurate data entry
  • No process or rules in application to validate data entry
  • Lack of Master Data Management (MDM) strategy
Examples:
  1. Phone number having values as 1111111111, 0000010100
  2. Customer Name as "ABC", "ZZZZ"
  3. Two records in a table like below:

Timothy, Kenny. 10 East Avenue

Tim, Kenny. 10 East Avenue

Impact of poor data quality:
  • Incomplete and misleading analysis
  • Increase in spending on incorrect data
  • Financial impacts when data is related to accounts and finance
  • Targeted market campaigns impacted adversely
  • Purchasing of data quality tools like First Logic, Trillium, etc.
  • Complicated ETL
  • Additional Cleansing in ETL process results in longer time to complete ETL cycle
Solutions for data quality:
  • Stringent data validations by means of rules in applications at source
  • Avoiding duplicate master entries by use of MDM solutions
  • If above not done, then using ETL process to handle data quality issues
  • Send feedback for bad data quality and correct at source, then reload
  • Maintain audit for data quality issues emerging from source systems
Data Cleansing Operations:
  • Removing invalid characters

remove extra and special characters from addresses, phone numbers, etc

  • Correcting data formats

formats for phone numbers, email addresses, etc

  • Identiying and removing duplicates
  • Building data quality audit and feedback system

record data quality in audit tables

automate process to send information of data quality to source system



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QlikView Licensing - an Overview


QlikView Licensing - an Overview

QlickView is an visualization and Dashboarding tool along with its own system.
There is a lot of confusion on how exactly QlikView provides licensing. Organizations take up trainings with QlikView and then they are told about it. I though it would be nice to know thing free of cost on internet.

There are basically 4 types of QlikView license
QlikView Personal Edition:
downloadqlikview


The QlikView Personal Edition allows you to create QlikView documents using available free source connections. Free, as in, the connectors for which all sources are free. Example: SAP conncetor will need additional purchase. The documents created on one Personal Edition can only be worked upon on same edition/machine. You cannot create it at one place and edit at other. It is, by all means, Personal.

QlikView Desktop Edition:
The QlikView Desktop Edition is for a small organization who does not want any server but does need multiple people work on same QlikView document. Sharing of documents is allowed.

QlikView Enterprise Edition:
The QlikView Enterprise Edition is for organizations which need to have a central place for development and update of QlikView documents. Consider this as central repository of all the developments. Here, all users have access to same set of data in QlikView documents.

QlikView Publisher:
The QlikView Publisher is an addition to QlikView enterprise. It enables having end users access only certain amount of data from QlikView documents stored on Enterprise server. The amount of data is manager by roles and restrictions.

There is also a thing called "License lease" where an Enterprise can manage which all QLikView Desktops can connect to the central server.

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