How Data Sourcing is the Building Block of Effective Business Intelligence
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Experts predict that the world will generate 120 zettabytes of data in 2023. Given the tremendous amount of data from so many sources, how can a business decide what is useful data and what should be ignored? After all, it’s your data that helps you analyze different aspects of your business and can drive informed business decisions.
The data you source can come from diverse sources. Customer behavior, website traffic, social media – the list goes on. Having a good data sourcing policy is the first step to effective business intelligence for your organization.
Just what is data sourcing though? And perhaps more importantly, how can you use data sourcing to ensure that your business decisions are built on good data?
What is data sourcing?
Put simply, data sourcing is the process your organization uses to collect and use relevant data. That data can come from both internal and external sources. It’s used to create your data infrastructure that then dictates your common workflows and helps you achieve business objectives.
With so much data being produced, it can almost seem like an impossible task to source the data you want and need. But sorting the wheat from the chaff is not as difficult as it may appear. The first thing is to understand the types of data you want to be using.
Data falls into two primary categories:
Primary data. This is data that you yourself will generate. It will usually focus on narrow categories such as specific problems or questions. This primary data could be generated by surveys, interviews, or anything that helps provide feedback that you have created to obtain the answers you need.
Secondary data. As the name suggests, this is data that is generated outside your business. It can come from a diverse range of sources such as research papers, books, etc.
Secondary data can itself be broken down into two categories:
Internal. Although created by others, this is data that already exists within your systems. In most cases, it will be found within your CRM system and comprises historical records of past and current customers.
External. This is data that is publicly available that lies outside your CRM. Your staff can collect this as needed or you can engage with a specialist data provider to source what you need.
Of course, you want any data you source to be of high quality. Low-quality data will not offer you the data information and insights you need and could lead to poor decisions.
Your methods of data sourcing can depend on the size of your organization. A larger company may have a dedicated team whose sole task is data sourcing (and ensuring that data quality is maintained). Smaller businesses may outsource their data sourcing to a specialist agency.
Remember, low-quality data is something that can lead to poor business intelligence and can in turn lead to costing you money in terms of lost revenue. So, when you are looking at data sourcing, you need to prioritize quality. Every data set you use has to be of the highest quality. For example, if you are using a snowflake schema to handle large amounts of data, even a small amount of low-quality data could throw the ‘results’ off.
Good data sourcing
A robust data-sourcing policy ensures that you’re extracting data only from consistently reliable sources. This guarantees that you make business intelligence (BI) decisions based on data that is valid and relevant. Most markets are highly competitive so any sort of edge on your competitors can future-proof your company.
Let’s assume you are sourcing data from reliable, high-quality sources, what comes next?
Great analytics. There is little point in having high-quality data if it’s not being analyzed properly. You need insights into how that data came about. What internal and external environmental factors affected it? In-depth analytics can vastly improve your BI and can help you make more informed business decisions..
Clear purpose. It’s not just a case of using data sourcing to collect massive amounts of data, even if it’s good quality. You need to have a clear purpose defined for any use of data. Do you want to improve sales revenue or website traffic, for example? Knowing what you want to achieve from data use is crucial.
Business data visualization. Effective business data visualization is another key component of this clarity. Visualizing your data in meaningful ways through charts, graphs, and dashboards can provide a clear and concise way to communicate insights to your team and stakeholders. This visual representation of data can aid in making more informed business decisions and enhancing your overall business intelligence strategy.
Business type. Your business type can help define your purpose and also the sort of data that will be most useful to you. You need some idea of your data orchestration process. Where is your data coming from and how will you organize and use it?
Data sourcing benefits
Moving forward, once you have good data sourcing in place and are sure of the quality of the data you’re analyzing, what benefits should you expect to see?
Cost savings. Good analytics can help you see what works and what doesn’t. You can streamline processes and see operational cost savings.
Better partnerships. Understanding what your partners (be they suppliers or clients) want and need through data analysis means you can build stronger, long-lasting relationships.
Demand forecasting. The ability to forecast demand through identifying patterns and cycles means you are more equipped to meet future demand.
Increases in efficiency. Are all your internal procedures and workflows working as well as they can? Good data sourcing means better BI. This in turn allows you to make tweaks where needed that lead to better efficiency.
Improvements to your supply chain. While the occasional logjam or issue may be unavoidable, others can be fixed. Insights into your supply chain can drive improvements to things such as lead times when ordering new supplies.
Better collaboration. As well as workflows, you may want to see if you can improve how teams collaborate with each other and to reduce the impact of silos. Even something as simple as identifying that a business phone number system will bring benefits can help with this.
Risk and compliance. Are you fully meeting risk management or compliance requirements in areas such as big data privacy? With good data sourcing and the resulting analytics, you can ensure that any such requirements are fully met.
With so much data available, it’s essential that your data sourcing strategy not only recognizes the volume of data available but also how to cherry-pick the data that matters to you. With good data sourcing and efficient analytics, you can improve your BI so that any operational decisions you make are ones that benefit you and your customers.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.