Published On June 4, 2019
The proliferation of data that is now available to businesses is a cross industry phenomenon. As more data becomes available, it becomes incumbent on businesses to gather that data, analyze it, and leverage it to make better business decisions. As such, data analytics has become critical to firms in helping to gain and then maintain competitive advantages.
Having established the criticality of data analytics, the challenge is in properly executing the associated processes. The data analytics journey has many steps in it and each step needs to be properly executed for firms to maximize results. Data collection, cleansing and aggregation are key foundational steps that must result in both holistic and accurate data. Harnessing all the available internal data within a firm, as well as the relevant external data elements, can be quite a daunting task. Establishing best practices for data management and data governance is something that will give this process the best chance for success. A mid-stage task within the journey is then applying appropriate data science and analytics to the requisite data. Using the right models and methods to drive insights for the business that will enable the business leaders to make better decisions around their products, customers and the competitive landscape. Having completed these first few stages, all this work must be encapsulated in an easily consumable format for internal stakeholders. A good BI/visualization strategy puts the proper finishing touches on the data analytics journey.
SGA and our data analytics solutions
Where SGA has been able to help firms is in building a complete platform, with multiple data pipelines feeding into that platform, that serves as a hub for their data analytics teams. Creating an automated data collection, cleansing and aggregating process, driven by business rules, enables client stakeholders to focus their efforts on value added tasks. Then, with the use of AI and machine learning, we have built models for our customers that enable them to interpret the data they have and make better business decisions. Using the proper data science methods and methodology to differentiate between a compelling trend that must be addressed versus an anomaly that a firm shouldn’t over react to. These are the types of business choices that can either enhance or damage a firm’s position in the marketplace. This whole process, when done properly, can change the paradigm for many firms into making data driven decisions that are fully supported by facts and historical models.
Please join us on the second episode of SGA Perspectives as we delve into more detail into the changes many industries are going through in data analytics, the types of business problems they are looking to solve, and the types of challenges firms have in building these platforms. We welcome your comments and feedback.