Monday, June 17, 2013

Data Quality, Data Management

In today's business world, there is a tremendous growth of data, there is lot of talk and use of Big data methodologies and tools. In order for data to be meaningful and effective it is very important to have data quality and data management standards. There is lot of data flowing through an organisation, how can be i maintained, how are the security concerns going to be handled, what is the value added proposition once can get from the data, these are the questions that need to be answered. One of the first things to do is create a data dictionary which would be a repository of all the sourcing that is done with all the object and attribute level information. The data dictionary could be part of a MetaData database, where in the datadictionary tables can be maintained. The datadictionary would contain information regarding the following areas:
Source of Data
Domain of the Data
Subject/Area of the data
Type of Source: Text Files/Excel/Sharepoint/Database
Frequency of Feeds
Target Database/Tables
Target Type
Attribute Information
Business Contact
Technology Contact

Capturing the above areas in data dictionary would help in maintaining what is being made available in the system. It would prevent data duplication and also give a sense of capacity and what type of data elements are being used. One of the key aspects that need to be paid attention to is how much of storage is being used and would help plan the capacity of data provisioning systems. In addition to maintaining data dictionary is application of data quality standards. What type of data quality is being implemented this could be from the basic checking of columns to complex business rules to determine if the data coming in good. It would be good to have a group which takes responsibility of data governance and quality. It becomes extremely crucial to have such standards in the growing world of data.

Monday, June 10, 2013

BI Multidimensional vs Tabular...Part 2

There is a constant debate about the direction of BI tools from Microsoft, which model will they support, the SSAS multidimensional or the office based Self service BI. There have been passionate exchanges on what will happen to SSAS multidimensional. Well recently in SQL Server 2012 there has been a new functionality that has been released. As part of SQL Server 2012 SP1 CU4, new functionality has been released that means that Power View now works with Analysis Services Multidimensional . Please go through the following link for more technical details:
As per the MSDN blog: Now Power View users can connect to both the tabular and multidimensional formats of the BI Semantic Model. This is achieved through native support for Data Analysis Expressions (DAX) in Analysis Services multidimensional models, ensuring optimal performance and functionality.

As per Chris webb a leading SQL Server BI expert: This is the first significant bit of new functionality in Analysis Services Multidimensional for a long while, and it acts as a bridge between the classic SQL Server BI stack that most of us are using and the brave new world of Office/Sharepoint-led BI. Please go through his comments on this functionality Here:

Monday, June 3, 2013

BI Solution-Gathering Requirements

In any project when one is trying to build a target state solution it is important to gather the requirements in a effective way. Very often it is a challenge to gather effective requirements. With respect to building BI solutions it is always preferred to have good requirements. BI Solutions are closely tied with business performance and also provide them capability to do analytics. Here is a link, an article written by SQL Server Expert James Serra on gathering requirements for BI Solution.
It is a very exhaustive list, it provides a good perspective on how to approach requirements gathering.