Introduction
If you are a company that deals with huge quantities of data daily, you are in certain need of solutions that will also manage it. In a world where almost everything we do is documented and tracked via our phones, smart devices, etc., data presents a big opportunity, but also responsibility for some companies.
In a business that offers products and services tailored by your data, your habits, and behaviour, managing that information poses an integral part of how the customer value is delivered. The end result is heavily dependent on how you collected, managed, structured, interpreted, and delivered that data. It is a most relevant resource, not only for forming better products and services but also for creating business strategies.
If we are talking about products and services that work primarily based on user data, then we can not disregard the importance of data management in delivering a better user experience. Because, in the end, how the customer views our products and services is an indication of whether we have a business success story or not.
Usually, in companies where data makes up the core business value, all the information and relevant sources are kept in databases and some companies might use more than one to store it. The issue occurs when data is not formatted the same and couldn’t be easily aggregated. In that instance, you would need a solution on how to use the information from those databases in a cohesive way that will show relevant and accurate metrics, and allow different analyses.
Cooperation with Bellabeat
For us, an opportunity arose when Bellabeat, a company that develops wearables and accompanying products that monitor biometric and lifestyle data, decided to cooperate with us in managing and analyzing that same data to provide more accurate and meaningful metrics to its users.
Their devices and their application collect daily information from their users that track health and their behaviour, and based on that it provides insights and relevant metrics that help manage their life and habits. When you collect that much data, you need to develop and use tools and solutions to convert it into accurate metrics that will keep up with product users. But firstly, certain data discovery and management were primary focuses before delivering the end result. Recognising relevant and identifying bad data became the basis for upcoming data aggregation. When there is a company such as Bellabeat that uses data to drive the product and user experience, using data science to read, shape, and interpret information into meaningful insights proves to be integral before any action is applied. If you want the end result to be precise and insightful, how you approach data is just as important. Combing through it and structuring it is a complex process, but there isn’t another way to deliver specific and accurate metrics. For example, if your current usage of data presents one result but it hasn’t taken into account all the data or it used bad data, the metric displayed to the user will not be completely applicable. For such instances, a data scientist could recognize deviations and irregularities, analyze them and come up with a solution that puts everything into perspective. Adding another set of data that wasn’t utilized before could also improve metrics and insights and deliver better results. When customer satisfaction depends on how data is processed, data science seems to take a leading role in it.
What Bellabeat wanted to accomplish with this is to improve metrics, engage users, improve user experience and define new metrics. As they are focused on improving the delivery of great value to the customer, enlisting us as collaborators to help them achieve their goals through building data warehouses and optimizing data for analytics, proved that businesses will need data engineering services.
Recognizing opportunities, as Bellabeat did, means that your business has a clear goal in mind and that you thrive on providing the best user experience and metrics to improve your customers’ lifestyles. It also helps you stay one step ahead of your competitors and allows you to strategize more clearly.
Data challenges
Data-based companies will always depend on how information is processed and what they can get out of it. For that, they’ll need expertise that goes beyond just data collecting since not all of it is easily manageable. Having multiple data sources and databases means it’s a bit more demanding to gather information, develop algorithms and methods to analyse it. Data could be differently measured and expressed in different values, and that proposes challenges in finding a unified way in its organization and interpretation.
Data quality is also a relevant issue. Sometimes companies gather information that is not always correct, complete, or reliable. On certain occasions, that information is taken into account and could display incorrect or irrelevant data. That kind of data could be filtered or corrected by using certain algorithms. The main goal is to end up with relevant and reliable data that could be used to deliver specific results and metrics.
These are the solutions that we bring to the table while helping you understand your data better in order to make more accurate data-driven decisions. But it’s not only the company that relies on data. In the case of Bellabeat, data is necessary to deliver certain metrics to the user. When you have so much information, it is not easy to interpret it. It is important to form data into cohesive and understandable metrics that anyone could use. The end-user is not interested in tables and unfiltered data. Information on its own is not as appealing and usable as a certain metric that was developed using more than one source of information. Data should be presented clearly and concisely and it should not leave any room for wrong or imprecise interpretation. A data scientist’s main goal is to simplify complex processes and data by using and improving certain algorithms that deliver clear and easily understandable results. Any way you put it, data science revolves around the end-user and the delivery of insights that will improve user experience.
That being said, not everyone recognizes the need for structured solutions for data gathering. Data scientists and engineers could help your business take on a serious approach to creating data collection processes, standardizing and organizing it so it’s understandable and analysable while also utilizing that collected data for making meaningful strategic decisions.
Conclusion
If the trends are anything to go by, data engineering and data science will take up even more space in business development than it already has. With technology showing only an upward trend, keeping up with it will demand the usage of information and data for building sustainable solutions that will support any business venture. Soon, businesses will be overrun by data from the market, customers (potential and own), the supply chain, and from within the company. All of that will show an immediate need for data science. Quick reaction to that will absolutely give any business a competitive advantage on the market.
Having great support is going to be vital as businesses grow through technology uproar and having a reliable data engineer or scientist will determine if the outcome is going to be successful.
