When it comes to data analytics, you need to consider advanced elements like data science and machine learning. However, before considering these elements for business success, you need to get down to database infrastructure basics.
The database infrastructure you choose should be strong enough to support both present and future data analytics requirements.
Note, this guide is not a sequential or an extensive list. It is rather a collection of ideas that highly qualified and skilled database administrators embrace for their clients’ benefit.
The need to start from the beginning
When it comes to business intelligence and any project that revolves around it, you need to consider the following questions:
- Do you have a strategy for data analytics in place?
- What is the total corporate strategy for your organization?
- What is your reason for data analytics?
As a business owner, you would need to define the technologies, business processes, and the people chosen to meet the goals of data analytics for your business.
The following approach helps businesses to define their data and its strategy for analytics:
- Understand the business vision: Determine your business’s long-term analytics vision and find out how it fits into your total business strategy?
- Capture your present position: This point covers interviewing your business stakeholders, assessing the sources of data, and reviewing the technologies currently in practice.
- Develop a plan for Data Analytics: This should be an extensive plan that gives you a road map as to where your business desires to go and the plan intended to fill the gaps that prevent you from reaching those goals.
- Deliver the desired results: The results by credible companies specializing in database administration and management are generally delivered in phrases for their clients to offer their valuable feedback through the whole process to get results all through the way.
If you do not have an extensive strategy for data analytics, you should commence making one. The following are some elements that you should include are:
- Gather business requirements and request DBA professionals to document findings instead of asking them to show you what you need.
- Professionals who work with you on your data strategy will begin to make a list of the source systems. They will interview the business to comprehend data sources and the departments that make use of them.
Give priority to projects
Make sure the projects for data analytics are prioritized well. In its absence, your projects will take unexpected turns that make the business goals get off track.
The following are the key reasons for you to prioritize:
- The success rates of strategic projects increase.
- The focus and the alignment of data management improve, especially when it comes to the fulfillment of strategic goals.
- Doubts are mitigated for all the database management teams when they need to make decisions.
- Generates a mindset for execution and good business culture.
Creating the right data model
The correct data model helps you to make the database structure where the information can stay in. This model needs to be created with a thought to give the business flexibility and simplicity of use. It will also define how the items are organized and labeled. This helps the business to determine how their data can be used and the findings it will tell.
A good data model will help the business define the issues to consider different approaches and select the best one for problem resolution.
Reasons for your business to have a data warehouse
Given below are the top reasons as to why your business needs a data warehouse:
- You do not have to access sources for data individually. This step reduces the preparation of excess data.
- The integration of sources with disparate data with general attributes is automatic.
- A credible data warehouse is created in such a way that humans can understand it. It is not created for any computer software program to understand it.
- Reduces the time for you to analyze the data. It offers you the confidence you want with real data and gives you valuable insights along with enhanced data security.
- Facilitates better data governance and curbs random data analysis that might not be accurate in findings.
The need for a data governance program
As a business owner, you must have a proper data governance program incorporated into your organization. It will help you attain consistency, accelerate the time for delivery, reduce the data maintenance requirements, get higher quality data, boost user engagement, and much more.
The data governance program is a significant piece to your data and its analytics solutions, and it is one of the most overlooked areas by modern business owners today.
The data governance program should have an outlined roadmap that includes the following steps:
- Integrate the data governance with other efforts for data.
- Design the metrics for data governance and its requirements for reporting.
- Define the requirements for sustaining the data governance program.
- Design an effective plan for change management.
- Define the operational program roll-out accurately.
The team that deals with data governance should work closely to ensure that the above program stays effective while meeting or exceeding expectations. It should be completely internalized and deeply ingrained in the organization.
As a business owner, you need to ensure the transformation management from data assets that are not governed to the governed data assets is conducted effectively.
Once the above plan is effectively rolled out and execution for change management executed, its framework should be examined for effectiveness. Note that data governance is not a self-sustaining practice. It should be created in such a way that it can naturally adapt to the business changes with success.
Business owners can consult qualified and skilled database management and administration professionals for guidance on the data governance program for their companies’ effective operations in the long run.
