Data Warehouse (DWH) implementation has to empower businesses and how would it?

It is created and brought in play to empower and accelerate the decision-making process and ultimately transform businesses. So, the key is steering towards the right approach for an effective implementation process. A DWH solution has to translate into ease in data retrieval with the desired output/presentation. How do we make this happen?

Today more and more organisations are focusing on data warehousing (DWH) solutions for streamlining their processes, connecting with various stakeholders, cost-effectiveness, upgradation and innovation in product offerings. Data warehousing (DWH) is a patterned collation of data designed and structured to enhance decision making process and make informed choices for a much more confident business decision.

Initially, this was regarded expertise of trained specialists, but with advancements in new agile Data Warehouse (DWH) technologies & tools it seems to be a feasible option for users with specific business needs. Structured formats with segmented information can be available over emails.

Nevertheless, the below mentioned points lay a foundation for successful DWH implementation. At the core is the approach and the focus that you would consider.

• Understanding current ongoing processes: The basic and initial step in any project is to have a detailed study of the present scenario. An analysis of the different databases currently maintained in the organisation, the interrelationships between different systems, etc. have to be undertaken for smooth and consistent progress. Moreover, the basic objective of implementing the DWH tool has to be defined.

• Checking heterogeneous systems: Generally, the data exists in duplication at different locations in different headings and formats. This requires a thorough study and scrutiny of the data. The duplicity would lead to errors, needs to be eliminated.

• Scrutinizing data quality: Using metadata to improve data quality. Metadata is ‘data about the data’. It gives information about the characteristics of the data contents. Metadata has the potential to create a central repository that can be used to provide information both for admin and users.

• Implementing the right tools: The tools extract data from different sources, transform it for use and storage along with the track info about the data. A tool that summarises data for analysis, performs error check, maps data to the source, tracks and manages the interrelated data is the need of the hour.

• Capturing a comprehensive view of the situation: Each and every system is connected with others in the ecosystem. External processes and transactions also generate related data that has to be considered while analysing and reaching a conclusion.

• Delivering the required relevant information: The information can be delivered in prescribed formats as desired by the users without depending on skilled analysts. Only the relevant information is shared with the users minimising the network traffic.

• Considering outsourcing as a viable option: The outsourcing team brings along their experiences and ideas from the previous assignments in solving the tasks and issues at hand.

The technology is just the tip of the iceberg, which encompasses a massive amount of data collected through the business processes of the organisation. DWH touches the organisation at all levels for data collection and management. Selecting the right tool with a focused objective is key to successful DWH implementation.Data Warehouse (DWH) implementation has to empower businesses and how would it?
It is created and brought in play to empower and accelerate the decision-making process and ultimately transform businesses. So, the key is steering towards the right approach for an effective implementation process. A DWH solution has to translate into ease in data retrieval with the desired output / presentation. How do we make this happen?
Today more and more organisations are focusing on data warehousing (DWH) solutions for streamlining their processes, connecting with various stakeholders, cost-effectiveness, upgradation and innovation in product offerings. Data warehousing (DWH) is a patterned collation of data designed and structured to enhance decision making process and make informed choices for a much more confident business decision.
Initially, this was regarded expertise of trained specialists, but with advancements in new agile Data Warehouse (DWH) technologies & tools it seems to be a feasible option for users with specific business needs. Structured formats with segmented information can be available over emails.
Nevertheless, the below mentioned points lay foundation for successful DWH implementation. At the core is the approach and the focus that you would consider.

• Understanding current ongoing processes: The basic and initial step in any project is to have a detailed study of the present scenario. An analysis of the different databases currently maintained in the organisation, the interrelationships between different systems, etc. have to be undertaken for smooth and consistent progress. Moreover, the basic objective of implementing DWH tool has to be defined.

• Checking heterogeneous systems: Generally the data exists in duplication at different locations in different headings and formats. This requires a thorough study and scrutiny of the data. The duplicity would lead to errors, needs to be eliminated.

• Scrutinizing data quality: Using metadata to improve data quality. Metadata is ‘data about the data’. It gives information about the characteristics of the data contents. Metadata has the potential to create a central repository that can be used to provide information both for admin and users.

• Implementing the right tools: The tools extract data from different sources, transform it for use and storage along with the track info about the data. A tool which summarises data for analysis, performs error check, maps data to source, tracks and manages the interrelated data is the need of the hour.

• Capturing comprehensive view of the situation: Each and every system is connected with others in the ecosystem. External processes and transactions also generate related data which has to be considered while analysing and reaching a conclusion.

• Delivering the required relevant information: The information can be delivered in prescribed formats as desired by the users without depending on skilled analysts. Only the relevant information is shared with the users minimising the network traffic.

• Considering outsourcing as a viable option: Outsourcing team brings along their experiences and ideas from the previous assignments in solving the tasks and issues at hand.

The technology is just the tip of the iceberg, which encompasses massive amount of data collected through the business processes of the organisation. DWH touches the organisation at all levels for data collection and management. Selecting the right tool with a focused objective is key to successful DWH implementation.[:]