Implementing Decision Support Technology with Microsoft SQL

This report details the implementation of business intelligence using Microsoft SQL Server for a data warehouse prototype. It covers key aspects such as data warehousing with Microsoft SQL, Microsoft business intelligence tools, prototype development, test planning, and data connectivity configuration. The report emphasizes the use of SQL Server for cleansing, collecting, processing, and analyzing data to support decision-making processes. It also explains how to extract, transform, and load data into the data warehouse, including configuring data connectivity and optimizing data storage. The goal is to successfully implement business intelligence and develop a functional prototype using Microsoft SQL.

Decision Support Technology

Table of Contents
1. Introduction.........................................................................................................................................3
2. Data warehouse with Microsoft SQL...................................................................................................3
3. Microsoft business intelligence............................................................................................................4
4. Data warehouse prototype...................................................................................................................5
5. Test plan of data warehouse.................................................................................................................5
6. Configure data connectivity.................................................................................................................6
7. Conclusion...........................................................................................................................................7
References...................................................................................................................................................8

1. Introduction
The main objective of this report to implement the business intelligence of data ware house
prototype by using the Microsoft SQL server. The business intelligence can be performing on
high business application tools can be used for cleansing, collecting, processing and analyzing of
the data. The evaluating and understanding the results is essential for the efficiency of decisional
system. Creating the knowledge of business intelligence and collecting form the data on internal
or external sources. Business intelligence is an entire concept can be implementing by the
decision support system. The decision support system can be used for the operation of
transactional system. The collecting the each data can used for databank and can processing of
resulting information can be stored on the data warehouse prototype. So the existing of DW was
necessary as the transactional database were unable to store the accumulated historical data. The
DW can be accessed by proper data analyzed and stored required data can preformed on the
prototype it will be investigated.
2. Data warehouse with Microsoft SQL
The SQL data warehouse is based on the cloud based enterprise data warehouse that can be
used for the leverages massively parallel processing (MPP) to can be quickly run complex
queries on the pet bytes of data. The data ware house is mainly used for the Analyzing of each
data can be stored on the database warehousing system (Berry, 2011). The source data can locate
on the Microsoft SQL server. The performing of the each data can be follows the steps includes
are,
 Pipeline data
 Export the data from SQL server
 Copy the data into blob storage
 Load data into sql data warehouse
The pipeline data that are used in the steps likewise,
 The export data on SQL server
 Copy the data files to move on Blob storage
 Loading the data on SQL data warehouse.
 Transforming data on the Datawarehourse prototype.
 Load the semantic model into analysis service (SQL server Data Tools)

Loading on the data can be following on two step process:
 Create a set of external table. External table can be used for the outside on the data can be
stored on data warehouse. In this case flat files occur in blob storage. This step does not
move any data into the warehouse can be used for ETL methods.
 The copy the data on data warehouse can be creating on the staging table and load the
data.
3. Microsoft business intelligence
The Microsoft business intelligence can be used for refer to a set of methods and
techniques that are used by databanks organization for tactical and strategic decision making
(Davis & Shaw, 2012). A data warehouse is simply a consolidation of data from a variety of
sources that is designed to support strategic and tactical decision making. The database can be

designed for query and analysis on rather than for transaction processing. It is usually contains
historical data derived from transaction data, but to can include data from the other sources.
4. Data warehouse prototype
The data ware house prototype is used for partial implementation of the system. The main
reason of to developing the prototype it is to resolve uncertainties of the development cycle of
data warehouse. The data warehouse prototype can be used for initial model of the development
lifecycle of software product using the SQL database. The planning of the prototype can be used
for the readily available to user application for querying and analysis. Data warehouse repository
of integrated information form distributed, autonomous and possibly heterogeneous sources. The
prototype can be used for the identifying data changes at heterogeneous sources, transforming
them and summarizing them in accordance to warehouse specifications, and incrementally
integrating them into warehouse (Emond, 2013).
5. Test plan of data warehouse
The testing planning of the data warehouse can be used on load the data that can follow the those
steps.
 Configure data connectivity
 Create the external data source

 Configure data format
 Creating the external tables
 Creating the schemas for the data
 Load the data on data ware house
 Optimized data stored compression
6. Configure data connectivity
The prototype can be configuring to the location and attributes of the external data. The all the
data can be stored in externally (Simmons, Stasiuk & Segarra, 2010).
The creating external source data command can be specified for location of the external data.
Configuring data format can be specified the format of the data in the text files.

Loading data can be used for the all the data can be stored on the data warehouse external
sources.
7. Conclusion
The main goal of this report to implementing successful on business intelligence and
development the prototype using Microsoft SQL. The business intelligence can be performing on
high business application tools can be used for cleansing, collecting, processing and analyzing of
the data. The evaluating and understanding the results is essential for the efficiency of decisional
system. The DW can be accessed by proper data analyzed and stored required data can preform
on the prototype to be successfully implemented.

References
Berry, G. (2011). SQL Server hardware. [S.l.]: Red Gate Books.
Davis, T., & Shaw, G. (2012). SQL server transaction log management. [Place of publication not
identified]: Simple Talk Pub.
Emond, N. (2013). Instant MDX Queries for SQL Server 2012. Packt Publishing.
Simmons, K., Stasiuk, C., & Segarra, J. (2010). Pro SQL server 2008 policy-based management.
Berkeley, Calif.: Apress.