Top 10 Advantages of building DW

At a very high level from data perspective, I am listing top 10 things what an organization gets when they start implementing the DW.

1. Organizations have the repository of operational data across enterprises

2. Integrated data is available for analysis

3. Management can get 360 degree of visualization

4. Historical data (current + previous versions of master records) exists

5. Enables the organization to answer any questions management has with little or no extra effort provided the data exists in the repository

6. Quality of data increases as we find gaps while integrating the operational systems

7. Enables the Ad hoc reporting for Analysis

8. Makes entire organization a data driven organization

9. Automation brings down the manual effort and it's ready to add any data provided there is a link

10. Evaluate your organization against the industry standard KPI's of your domain and make sure you are par with the way your competitor thinks and acts.

 

Stages of Data warehouse implementation

DW implementation evolves over the period of time in a company.

In the industry, we compare the implemenation with five stages. By comparing what the current DW is doing, we can visualize what else we can do with the DW to get maximum ROI (Return on Investment).

Typically in an organization, managers start asking various questions where there are no system can provide the information in one report or set of reports. In this scenario company hires a team of IT resources who can pull the information from various systems, put together reports manually by taking some time (it varies from 1 day to a week normally to get the result)

If the day today requirements from managers becomes more and more then its the time where company takes the decision to build a DW where the data is stored in a way that its easy for reporting and analysts can build the reports on the fly based on their requirments.


Stage1: What happend?

In this stage of DW, only static reports churn out from the reporting / MIS system.

Stage2: Why it happend?

In this stage, we are finding the reasons because of the facts. What happend will show the facts, why it happend will show the reasons on what happend. Here we use OLAP tools which enables us to visualize and drill down to detail levels and also allows us to create new reports on the fly.

Stage3: What will happen?

Prediction what is the future based on the past and current knowledge we gained from historical data. Usually we use Data Mining tools which gets data from the repository and apply mathematical / statistical functions on the data and predict the variable what you are looking for. For example, when a call goes out of call center or contact center, if the agent knows the probability of acceptance before making a call then he or she can pick the customers who has high probability. In this case, data mining tools will calculate the probability against each customer using an algorithm you choose.

Stage4: What is happening now compared to past?

Take the current data and match with past data and react accordingly in the operational systems. Here the feed from DW goes to operational systems which makes it more effective. The ROI of DW kicks in big time when we reach to this stage as your operations becomes very effective.

Stage5: Being Proactive instead of being reactive based on a scenario.

Here we send alerts / intimations to stakeholders based on the threshold values defined against each of the KPI's what business is looking for.