Portfolio By Jorge Gomez Danes

PROJECTS PORTFOLIO
The core goal of the following projects portfolio, is to introduce the reader to the work I have done in
the area of Business Intelligence / Data Warehouse through my four and half years of experience in this
field.

The following are five projects covering, Microsoft SQL Server 2000, DTS, Analysis Services, Microsoft
SSIS, SSAS, SSRP 2005, SharePoint and Performance Point Server 2007.

Other skills I developed during this time are the administration of appropriate work and the successful
execution of projects. Good communication with the team work as well with other coworkers. Abilities
to implement and use a new methodology work. Change adaptation work.

Projects Titile

1) Analysis, design, construction and implementation of a data warehouse for a company
dedicated to the baking industry, supported with technologies from Microsoft SQL Server, Data
Transformation Services, Analysis Services and Open Intelligence, using data mining models,
followed Business Dimensional Lifecycle proposed by Dr. Ralph Kimball ....................................... 2
2) Expand the application of The Business Intelligence for the departments of accounts payable,
accounts receivable and logistics. Making changes to current processes of actual ETL and OLAP
cubes. ............................................................................................................................................. 15
3) SetFocus Business Intelligence Project using Microsoft SQL Service Integration Services 2005 .. 26
4) SetFocus Business Intelligence Project using Microsoft SQL Service Analysis Services 2005 ....... 33
5) SetFocus Business Intelligence Project using Microsoft SQL Service Reporting Services 2005,
Performance Point Server and SharePoint Server ......................................................................... 40

1

Analysis, design, construction and implementation of a data
warehouse for a company dedicated to the baking industry,
supported with technologies from Microsoft SQL Server, Data
Transformation Services, Analysis Services and Open
Intelligence, using data mining models, followed Business
Dimensional Lifecycle proposed by Dr. Ralph Kimball

Introduction
Paper thesis for a professional diploma in computer systems engineering, in which the
implementation of the data warehouse is described in detail, through several chapters covering
the general description of the company, project justification, the framework, the five steps:
analysis, design, construction, testing and implementation of an information technology
project, supported by the business dimensional lifecycle proposed by Dr. Ralph Kimball and the
conclusion of project and future work.

This project shows how the organization carries out the implementation of Data Warehouse
architecture, which allowed them to perform complex analysis, better understand of the
organization and be able to make better decision in the sales, accounting, warehouse, accounts
payable and accounts receivable areas.

Audience
Focused on business intelligence developers, as well as any professional in the information
technology area. Any person who is involved in decision-making for the company.

Project Goals:
Create the necessary documentation for the processes of analysis, design, construction,
testing and implementation of data warehouse system.
Create the physical and logical architecture of the hardware and software for the
correct operation of data warehouse system.
Allow the extraction from the current data base systems, transform for the business
needed and loaded to dimensional database models.
Create dimensional cube based on business needs for sales, accounting, inventory,
accounts payable and accounts receivable.
Allow having a source of information of the data extracted safely and the ability to be
scalable over time.
Allow access to information (OLAP), to end users through tools such as Open
Intelligence or Microsoft Excel for the exploitation of information.

2

Actual Business Diagram

Explanation
This diagram show how the business works regarding to make the information analysis at the
end of each month and all the process from the extraction of the information trough standard
and complex query’s to the DB2 data base, the manipulation trough Macros on Excel and the
interpretation to make decisions.

3

Propose Business Diagram

Explanation
This diagram shows the workflow with the proposal and implementation of a data warehouse
system. ETL processes as well as the load on dimensional databases are present in this diagram.

4

Data Source Analysis

Command Module Files or Objects
Line
/GL Accountability FLP060 Parameters files (catalogs, etc. etc.)
FLP008 Detail Transaction Document
/OE Invoice and Orders OEP16 Price List
OEPDF Other Price List
OEP20 Customers Details
OEP40 Order Header
OEP55 Order Details
OEP65 Sales Header
OEP70 Sales Detail
/IN Warehouse INP10 Company Information
INP13 Warehouse Descriptions
INP15 Files Descriptions
INP35 Product Catalog
INP38 Product Catalog Others
INP95 Warehouse movements history
/AP Accounts Payable PLP05 Supplier Catalog
PLP15 Transaction Master
PLP20 Detail Transaction Master
PLP25 Session Control File
PLP45 Supplier Payment
/AR Accounts Receivable SLP05 Customer Master
SLP15 Transaction Master file
SLP20 History Transactional Master File
SLP25 Session control File

Explanation
This table shows the Data Source Structure of the DB2 for the JBA/AS400 mainframe.

5

Data Warehouse Bus Architecture Matrix

Dimensions

Transactions
Warehouse

Customer

Supplier
General

Product
Ledger

Zone
Date
Accounts
Payables X X X
Sales X X X X X
Data Mart

Purchases X X X X
Production X X X X
Warehouse X X X X
Accountability X X X
Taxes X X X

Explanation
This Architecture Bus shows how Dimensions cross with the Data Marts.

Logic Design of Sales Fact Table with Dimensional Table and the Attributes

Tabla de Hecho
VENTAS
Cliente Región

Tabla de Hecho Dimensiones
Ventas Cliente
Fecha
Granularidad Región
Snapshot Producto

Fecha Producto Atributos
Unidades
Monto
Costo
Margen de contribución *
Explanation
1) This Image show the relation between the Dimensional Tables of Customers, Date, Zone
and Products are related to the Fact Table of Sales that is the Data Mart of Sales
Department.

2) This Image Show the attributes for the Sales Fact Table that are, Units, Sold, Cost and
one derived column Gross profit.

6

Detail Product Dimension with logic description and Diagram.

Product Dimension
Attribute Description Changing Dimension Example
Name Product Name Slowly Changing DAWN RLL RD MANZANA 10.9
Type Product Type Slowly Changing Finished, Process, Raw Material
Category Product Category Slowly Changing Wet, Dry, Frozen, Other
Major Group Product Major Group Slowly Changing Flavor, Chocolate,
Division Product Division Slowly Changing Purchased, Produced
Presentation Product Presentation Slowly Changing EA, CS, BG

Dimensión
PRODUCTO

División Categoría
(2) (5)

Tipo Grupo Mayor
(7) (n)

Presentación Nombre del
(22) Producto

Explanation
1) The table shows the attributes name the description also if the dimension is a slowly
changing dimension and some examples of the information.

2) Show the logical and the hierarchy of the product dimension.

7

Data Source-Destination Table

Data File Field
Table Column Data Type Long Description
Source Source Name
Product
Surrogate Key Integer 6 Surrogate Key
Dimension N/A N/A N/A
Product
Code Varchar 12 Product Code PNUM35
Dimension JBA INP35
Product
Dimension Name Varchar 45 Product Name JBA INP35 PDES35
Product
Dimension Type Varchar 20 Product Type JBA INP35 PTYP35
Product Product
Dimension Category Varchar 15 Category JBA INP35 PCLS35
Product Product
Dimension Division Varchar 10 Division JBA INP35 DIVN35
Product Product
Dimension Presentation Varchar 2 Presentation JBA INP35 SUNT35
Product Product Major
Dimension Mayor Group Varchar 10 Group JBA INP35 PGMJ35

Tabla de Hecho
FVentas
Logic Attribute Physic Attribute
Dimensiones Name strDProducto_nombre
intDCliente_clave Type strDProducto_tipo
intDFecha_clave Category strDProducto_categoria
intDRegion_clave
intDProducto_clave
Mayor Group strDProducto_gpo_mayor
Division strDProducto_division
Atributos Presentation strDProducto_presentacion
intFVenta_unidad
intFVenta_venta
intFVenta_costo
intFVenta_margen *

Explanation
1) The first table show a more detail description of the product dimension table. The
source field into the DB2 Data Base and the data type of the columns.
2) The Image shows a better practice of how to name the attributes in the SQL Server
Table, for the int to integers, str, to string.
3) The second table shows the logic and physic attributes.

8

Web Services Configuration

Explanation
This is a Web Services configuration for ISAPI dlls files. These services allow run XML Analysis
Services app.

9

T-SQL Statements
Código SQL:
CREATE TABLE [dbo].[DProducto] (
[intDProducto_clave] [bigint] IDENTITY (1, 1) NOT NULL,
[strDProducto_codigo] [varchar] (12) COLLATE Traditional_Spanish_CI_AS NOT NULL,
[strDProducto_nombre] [varchar] (50) COLLATE Traditional_Spanish_CI_AS NOT NULL
[strDProducto_tipo] [varchar] (20) COLLATE Traditional_Spanish_CI_AS NOT NULL,
[strDProducto_categoria] [varchar] (10) COLLATE Traditional_Spanish_CI_AS NOT NULL,
[strDProducto_division] [varchar] (15) COLLATE Traditional_Spanish_CI_AS NOT NULL,
[strDProducto_presentacion] [varchar] (3) COLLATE Traditional_Spanish_CI_AS NOT NULL,
[strDProducto_gpo_mayor] [varchar] (20) COLLATE Traditional_Spanish_CI_AS NOT NULL
) ON [PRIMARY]
GO

CREATE TABLE [dbo].[FVenta] (
[intFCliente_clave] [bigint] NULL,
[intFProducto_clave] [bigint] NULL,
[intFFecha_clave] [bigint] NULL,
[intFRegion_clave] [bigint] NOT NULL,
[intFVenta_unidad] [int] NOT NULL,
[intFVenta_venta] [bigint] NOT NULL,
[intFVenta_costo] [bigint] NOT NULL,
[intFVenta_margen] [bigint] NOT NULL
) ON [PRIMARY]
GO

Explanation
1) T-SQL statements to create the product dimension table and the sales fact table.
2) ETL Process for the creation of all the Dimensions, reading from flat files and DB2
sources.

10

Visual Basic Script
Function Main()
DTSDestination("intDCliente_limite_credito") = Trim(DTSSource("CRLM05") )
DTSDestination("strDCliente_mkt_channel") = Trim(DTSSource("CGP105"))
DTSDestination("strDCliente_vendedor") = Trim(DTSSource("DESC6001"))
DTSDestination("strDCliente_grupo") = Trim(DTSSource("DESC60"))
DTSDestination("strDCliente_tipo") = Trim(DTSSource("DSCL63"))
DTSDestination("strDCliente_codigo") = Trim(DTSSource("CUSN05")) + Trim(DTSSource("DSEQ05"))
DTSDestination("strDCliente_corporativo") = Trim(DTSSource("CUSN05")) +" "+ Trim(DTSSource("CNAM05"))

if (Trim(DTSSource("CAD105")) = "") then
DTSDestination("strDCliente_nombre") = Trim(DTSSource("DSEQ05"))+ " " + Trim(DTSSource("CNAM05"))
else
DTSDestination("strDCliente_nombre") = Trim(DTSSource("DSEQ05"))+ " " + Trim(DTSSource("CAD105"))
end if

Main = DTSTransformStat_OK
End Function

1) Visual Basic Script for a transformation for the Customer Dimension Table.
2) ETL Process for Sales Fact Table.

11

Metadata from Analysis Services

Explanation
Metadata information from the result of processing the information in the Analysis Services.

12

Data Warehouse Architecture

Example Report from OLAP Data Base

Explanation
1) The first image shows up the General Data Warehouse Architecture of how was built.
2) The second image represents a Corporate Sales Report in with the Gross profit % BTW
years for the amount sold.

13

Extra information
The result of this project ends in my thesis documentation with a deeply research of how to
implement a BI Project and also I made it. This book is around five hundred pages and what it’s
presented in this portfolio is only 5% or less of the completed work.

The completed work was made it in the Spanish language, if one who is interested in review the
work, can make a request and make the necessary translation of the electronic PDF file.

This PDF file can be requested by email at, Jorge.gomezdanes@gmail.com.

The Chapters below are available.

Chapters

1) Book cover
2) Acknowledgments, Dedication and Prologue
3) Index
4) Summary
5) Introduction, Company and Project Justification
6) Framework (Methodology)
7) Analysis and Design
8) Construction
9) Testing, Deployment, Conclusion, Future Work
10) References
11) Annexes

The PDF file provided by Jorge Arturo Gómez-Danes Mejia are copyrighted and is illegal to
copy, use, duplicated or distribute without the consent letter signed by the principal author.

14

Expand the application of The Business Intelligence for the
departments of accounts payable, accounts receivable and
logistics. Making changes to current processes of actual ETL
and OLAP cubes.

Introduction
Once the organization has started to use the services and benefits of the Business Intelligence
systems, it’s when the desire arises to replicate it to other departments. This project shows
complex structures to the new implementation in the particular process of ETL, OLAP and MDX.
It also presents the documentation for those activities and process.

What happens to the outstanding balances on an account receivable in which the customer has
credit days and OLAP cube must be able to show customer's current balance, outstanding
balance, aging days and balances to overcome periods of 30, 60 or 90 working days depending
on the company metrics? We need to have a many transformations and calculations in the ETL
process as well in the MDX language.

Audience
Focused on Business Intelligence developers, any IT professional, as well any management level
in the accounts receivable, accounts payable and logistic departments.

Project Goals:
Create dimensional data structures suitable for the ETL process.
Create new ETL processes that meet the requirements of the organization to implement
data marts.
Create new Dimensional OLAP cubes that meet the requirements of the organization.
Perform the necessary tests to create new processes.
Making changes to current processes of ETL and OLAP cubes.
Generate relevant documentation to support the work mentioned above.

15

Data Warehouse Tables

Explanation
Data base dimensional and fact tables.

16

DTS Packages

Explanation
List of the DTS packages. We have here the dimensional process and the fact table process for
logistics, sales, accounts payables, accounts receivable, warehouse and accountability.

17

Specific DTS for the account receivable process

Explanation
In this complex process, we have two connection managers, first from the AS400 DB2 database,
second from the SQL Server database. Also the image shows many T-SQL statements for:
truncate tables, create temporal tables, extraction of the information, some core process to
load the specific data of the accounts receivable information. For end process, it image shows
dimensional and cube OLAP process.

18

Account receivable T-SQL ETL code
DECLARE @Periodo As INT SET @strQry=@strQry+' where pper20<='+CAST(@Periodo As CHAR(5))+'
DECLARE @Sig As INT Group By LREF20, ETYP20) As A'
DECLARE @PeriodoIni As INT SET @strQry=@strQry+' WHERE BALANCE<>0 AND
DECLARE @PeriodoFin As INT pper20<='+CAST(@Periodo As CHAR(5))+')'
DECLARE @strQry AS VARCHAR(8000)
DECLARE @strUnion AS CHAR(10) SET @strUnion=' UNION '
DECLARE @UltimaFecha As DATETIME
SET @PeriodoIni= 10801 --CAST(CAST(DATEPART(YY,GETDATE())-1900 AS IF RIGHT(CAST(@Periodo AS CHAR(5)),2)=12
CHAR(3))+ '01' AS INT) BEGIN
SET @PeriodoFin= CAST(CAST(DATEPART(YY,GETDATE())-1900 AS SET @Periodo=@Periodo + 89
CHAR(3))+ RIGHT('00'+RTRIM(CAST(DATEPART(M,GETDATE()) AS END
CHAR(2))),2) AS INT) ELSE
BEGIN
SET @strUnion='' SET @Periodo=@Periodo + 1
SET @Periodo=@PeriodoIni END
SET @Sig=0
SET @strQry='' END

WHILE @Periodo<=@PeriodoFin --print @strQry
BEGIN EXEC(@strQry)

IF RIGHT(CAST(@Periodo AS CHAR(5)),2)=12
BEGIN
SET @Sig=@Periodo + 89
END
ELSE
BEGIN
SET @Sig=@Periodo + 1
END

SET @UltimaFecha = DATEADD(dd,-
1,CAST(CAST((CAST(SUBSTRING(CAST(@Sig As CHAR(5)),1,3) As INT) + 1900)
As CHAR(4))+'-'+SUBSTRING(CAST(@Sig As CHAR(5)),4,2)+'-01' As
DATETIME))
if @Periodo=@PeriodoFin
BEGIN
SET @UltimaFecha=GETDATE()
END

SET @strQry=@strQry+@strUnion+'SELECT [CONO20],'
SET @strQry=@strQry+'[CUSN20],'
SET @strQry=@strQry+'[ETYP20],'
SET @strQry=@strQry+'[LREF20],'
SET @strQry=@strQry+'[TTYP20],'
SET @strQry=@strQry+'[RCOD20],'
SET @strQry=@strQry+'[BTMT20],'
SET @strQry=@strQry+'[PTMT20],'
SET @strQry=@strQry+'[CURN20],'
SET @strQry=@strQry+'[DOCD20],'
SET @strQry=@strQry+'[SESN20],'
SET @strQry=@strQry+'[EVNT20],'
SET @strQry=@strQry+'[PPER20],'
SET @strQry=@strQry+CAST(@Periodo As CHAR(5))+' As Periodo,'
SET @strQry=@strQry+''''+rtrim(CAST(Datepart(dd,@UltimaFecha) AS
CHAR(2)))+'/'+rtrim(CAST(Datepart(mm,@UltimaFecha) As
CHAR(2)))+'/'+CAST(Datepart(YY,@UltimaFecha) AS CHAR(4))+''' As
FechaActual,'
SET @strQry=@strQry+'[CLRD20],'
SET @strQry=@strQry+'[VTMT20] FROM TEMPSLP20'
SET @strQry=@strQry+' WHERE LREF20+ETYP20 IN ('
SET @strQry=@strQry+'SELECT LREF20 + ETYP20 FROM ('
SET @strQry=@strQry+'select LREF20,ETYP20,sum(BTMT20) As BALANCE'
SET @strQry=@strQry+' from TEMPSLP20 '

19

Explanation
Before you run this query, you must remove all previous customers who have no outstanding
balances with the company, ie the sum of what you have paid and purchased are zero.
Subsequently, those who are carrying a balance, you perform a sum of all assets that have
outstanding balances for each period of the last 12 months. ie a January 2010, the total amount
of debt, to December 2009, the sum total of their debts, and so repeatedly to 12 months in
advance.

Since the end of each month, it is pertinent to consider that total debt is held by a customer
and what month comes each debt.

Account receivable T-SQL query process.

Update TEMPSLP20V2
SET BALANCE = A.BALANCE
FROM
(select sum(BTMT20) As BALANCE, MIN(LREF20) as DOCUMENTO, MIN(PERIODO) as PER,
MIN(ETYP20) as ENTRADA, MIN(EVNT20) as EVENTO
from TEMPSLP20V2
group by LREF20, ETYP20, PERIODO) as A
WHERE LREF20 = A.DOCUMENTO and PERIODO = A.PER and ETYP20 = A.ENTRADA and EVNT20
= A.EVENTO

Update TEMPSLP20V2
SET BALANCEUSD = A.BALANCE
FROM
(select sum(PTMT20) As BALANCE, MIN(LREF20) as DOCUMENTO, MIN(PERIODO) as PER,
MIN(ETYP20) as ENTRADA, MIN(EVNT20) as EVENTO
from TEMPSLP20V2
group by LREF20, ETYP20, PERIODO) as A
WHERE LREF20 = A.DOCUMENTO and PERIODO = A.PER and ETYP20 = A.ENTRADA and EVNT20
= A.EVENTO

Explanation
This T-SQL specific, shows the sum of the balance, among other fields, for clients who have debt
with the company for both USD and MXN currency.

NOTE: for this project there is not a solution to the types of changes. Each currency (MXN,
USD) was calculated.

20

OLAP Structure

Explanation

This images shows up the different kind of
OLAP cubes, and for the Account Receivable
Cube it shows the different kind of
dimensions and also are in hierarchies,
customer, date, transaction, mixes
dimensions.

21

Star Schema Diagram for Account Receivable

Explanation

Star schema with eight dimensions (Periods, Warehouse, Entry Type, Reason Codes, Zone, Date,
Customer and Sub Entry Type) and also into the fact table there are many kind of natural
measures, and we have two type of core measures, degenerate dimensions (order, invoice,
etc.) and normal measures (debts, balance, etc.)

22

Measures and Calculate members

Explanation

Natural measures and calculate measures. Many of the calculate members are evaluate the
same measure but with a different period the common use is for the last period.

23

MDX code and Drill Through options

Explanation

In this MDX expression we have many functions on it. Iif(), PrevMemeber(), CurrentMember()
NOT an operator and using the NULL values. This is very important because the PrevMember()
and CurrentMember(), we need to use the Date Dimension, and the Date Dimension need to be
set up as DateTime Dimensios Datatype, this is an important configuration.

Explanation
Columns that will appear in a drill through execution.

24

User Roles and Restricted Dimension access

Explanation
In the first image we have all the users that have a different access to the OLAP cubes and for
the second image we have a specific restriction to access just a one kind of granularity in the
customer dimension.

25

SetFocus Business Intelligence Project using Microsoft SQL
Service Integration Services 2005

Introduction
Create SSIS packages to extract information from excel and CVS files formats with Data Source and the
connection manager properly. Create specifics transformations tasks like data conversion, derived
columns, look up, conditional split and scripts tasks, as well with the correct precedent constraint and
pipelines. Create the upload of the information for new, existing and bad Id’s. Used of the notification
email. Deploy the packages and create a schedule jobs.

Audience
technology area.

Project Goals:
Review the source data (Excel or CVS). Make some enhancements to the existing data
sources, to support more flexible business practices for customer invoicing.

Use SQL Server 2005 Integration Services to integrate these external data sources into
the SQL Server database. (Using the specific task to create the necessary
transformation)

Create the necessary tests to the package as well execute successfully.

Create the specific documentation for each package (Documentation with the source,
destination, files to read, data base to load, process, results)

For each package generate a successful and failure emails using the variables for new,
updated or bad ids.

Create a maintenance package to backup, shrink and reindex the data base.

Use correct proper error handler as need it. Correct NULL statements, use of the new
rows Inserted using OLEDB Destination, updates using OLEDB Command, use
annotation, comments and best practice to name objects and variables.

26

Read several CVS files

Explanation

Package that read several CVS files from some path, made the transformation as need on each
one of them, create the necessary calculations with the variables and send a successful or
failure email.

27

Declaring and using variables

Explanation

The fist image show a list of variables used in the last package. The name and the scope and the
right type of data. And the second image shows a simple Visual Basic script of how use that
variables for each file read it.

28

Using several task into the Data Flow Tab

Explanation

There are 9 basic steps beginning with the extraction from an Excel source file, data conversion,
two lookup task and a conditional split. What in the lookup task want to do us to find that the
EmployeID exists into the BTW the source file and the data base using a JOIN statement for the
Employe table and EmployeRate Table. And for the second Lookup to identify what rows are
new or what rows are changed from the Unique Keys identifier.

29

Conditional Split task and Destination source.

Explanation

The image shows multiple conditions for proper error handler. If an EmployeeID is not present
in the source file or if the JobID is not present in the source file or if the WorkDate is grather or
equal than WorkClose, the three option go to a flat file destination and report in the with rows
are wrong.

And for the OLE DB Destination is for new rows and the OLE DB Command is for the updated
rows using the parameters as need in the configuration.

30

Manage all packages with Maintenance plan

Explanation

This is the master package, that executes a bunch of package with some ETL process and also it
includes a simple database maintenance plan with the emails associate with successfully and
failure.

31

Job scheduling

Explanation

The image above shows the basic configuration of a SQL Job, with a step and schedule
configuration for the master package. In this package the connection manager and the owner
of the SQL Job, was configured properly to run well every midnight.

32

Service Analysis Services 2005

Introduction
Created a SSAS solution in Microsoft Business Intelligence Developer Solution with four fact tables, five
dimensions, one of them with multiple hierarchies and five KPI’s. Created a MDX code solution in
Microsoft Management Studio. Develop and access the information from Microsoft Excel 2007 and
created five reports.

Audience
technology area.

Project Goals:
Created data sources and data sources view.

Created five dimensions.

Created multiple hierarchies relationship between one dimension and other data source
tables.

Created one cube with four fact tables.

Created eight calculate members

Created five KPI’s indicators.

Created two partitions for each fact table and aggregations up to 50%.

Deploy to SSAS Services and execute from Management Studio.

Written down 24 complex MDX code.

Created five reports on Microsoft Excel 2007.

33

Data Source View – Cube

Explanation
The first picture shows a data source diagram from the data staging area in the
database. Relationships between data base tables.
The second picture shows a cube diagram from the data source view. In this diagram we
can appreciate the four fact tables and only five dimension tables. We have a peculiar
difference btw the first and second picture, the number of tables. I will show the
difference in the next picture.

34

Job Master Dimension – Multiple relationships

Explanation

This picture shows a JobMaster.dim, dimension table that is related with other four tables. We
have here the configuration of the relationship between tables that are not part of a dimension
in a cube, but some attributes from other tables need to show up into the cube.

35

Dimensions Usage – Calculate Members

Explanation

The first picture shows how each fact table is related to each dimension into the cube
structure. In this structure we can see that the job Master and the All Works Calendar is
related for all fact tables, when the overhead, material types and employees is just
related into some of the fact tables.

The second picture is a list of some calculates members that were created for the cube
structure. In the next picture in the portfolio I will show how I can handle more and
complex MDX code.

36

KPI

Explanation

The image show how is set upped a the Open Receivables KPI , that is a value expresion for a
calculate member called Open Receivables and evaluated to be in a range of values to set a
goodterm, midterm and badterm values for a traffic light colors. KPIs and Trend are very usefull
to see some patterns in the history of the data.

37

Cube Partitions and Cube Browser

Explanation
The first image shows two partitions for each fact table and a 50% aggregations. Each
partition has a condition about historical and actual year.
The second image shows the cube browser for previous results evaluations

38

MDX Code

Explanation
MDX query’s for the CUBE structure and end-user ad-hoc requirements. I can handle many of
the MDX functions and also VBA, and Excel Functions.

39

Service Reporting Services 2005, Performance Point Server and
SharePoint Server

Introduction
End users need access tools to analyze information. This information can be from relational data
sources, dimensional data sources, OLAP cubes, Excel sheets, web information and also information in
flats files. Reporting Services as well Performance Point Server allow us to create a simple and complex
end users report. Also SharePoint Server is an intranet that let us to publish many of this reports in a
very structure way with many features. In this project I will show you what I have done and how.

Audience
Focused in business intelligence developers as well as any professional in the information
technology area and business end users.

Project Goals:
Created reports with SQL Server Report Server in Business Intelligence Developer
Studio, with information from relational databases and OLAP information. Created
parameters for those repots to be dynamic and also give the adequate format to
present the report.

Created reports on Performance Point Server with OLAP information. Created
Dashboards, KPI, Reports, with multiple parameters graphics, grids and Excel Services
reports.

Created reports with Excel, with pivot tables, pivot charts with multiple filters.

Created a Collation Site on SharePoint Server, with multiple documents library and
many subscriptions.

Deploy and publish all the reports for SQL Server Report Server, Performance Point
Server and Excel Services.

40

SQL Server Report Services – Data

Explanation

On SSRS, it is possible to define the dataset from we want to query and create the results
information that we want to build in the layout. We can use the OLAP information, relational
databases. Both types, automatic design and expert design to build the information that we
want to see. In this case with expert design with and MDX query.

41

SQL Server Report Services – Layout

Explanation

This is an important step. The developer need to know the tool to create the report layout
exactly what end user need to see, and also how to play with the different tool that SSRS have.
In this layout we can create, tables, matrix, charts, with many data sources, grouping
information, create summarize data, and give a fancy end users design.

42

Performance Point Server

Explanation

Performance Point Services allow us to create dashboards, KPI’s, Scorecards and Reports from
many data sources with different types of indicators as light or gauge. This image, show many
different objects, that I will show in next images but in SharePoint Server.

43

Share Point Server with Excel Services

Explanation

This image show two important things, the first one is the chart wit two different type of
indicator a percentage and a bar chart, created in Excel Services, then it show the background
of the SharePoint Server where it has many documents library with the different kind of
reports.

44

Reporting Services with Share Point

Explanation

This image show the way look SSRS deployed it in Share Point Server, with the parameters of
time and clients. It also show the grouping by client and the jobs worked by hours and total
labor cost.

45

Performance Point Server on SharePoint Server

Explanation

This image shows two KPI reports with one parameter in Share Point Server. This two KPI, are in
the image above in the Performance Point Server section.

46

Performance Point Server with Share Point Server

Explanation

This image shows two basic reports created on Performance Point server, but it had a particular
feature, the two reports are linked with the time parameter and the top 10 jobs and 5 workers.

47

Excel Services with SharePoint Server

Explanation

This image shows two reports created on Excel Services, a chart image with two measures and
the table for that chart image. The configuration in the Performance Point Server is important
because from there we can create the layout of how we want to show the information.

48

Portfolio By Jorge Gomez Danes

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