Fremont, CA: In today’s hyper-competitive business environment, nearly every organization is striving to become data-centric, leading many to dedicate a significant portion of their IT budgets to big data strategies. With enormous volumes of data generated daily, companies are increasingly focused on extracting actionable insights. Yet, the biggest challenge lies in determining the true commercial value of this data. Equally important is understanding how data intersects with technical expertise, a key factor for businesses aiming to fully leverage the potential of big data.
According to a poll, just 18 percent of organizations believe they have the capabilities needed to collect and apply insights effectively. In addition, only 19 percent believe their insights-gathering methods directly contribute to sales effectiveness.
Data, regardless of size, is undeniably the new oil for organizations. Data science is essential for making this data useful and actionable for business stakeholders. In addition, as other technologies benefit from big data, such as business intelligence dashboards and reporting, data science will reveal its actual usefulness.
How to Extract Most from Big Data
Many IT administrators lack a comprehensive grasp of the data possible to profit from big data. Moreover, the absence of resources and ideas about what to do with such data once it has been collected makes extracting corporate value difficult. In this setting, data scientists and analytics executives who understand the company and have a clear picture of the objectives may proactively propose ideas and choices.
When it comes to determining which data has to be translated to increase company value, recognizing business effects based on analytical insights necessitates bringing together the proper set of individuals with upgraded talents and then establishing the vital connections between them. Furthermore, exploiting the data hierarchy demonstrates that the true value of data lies in experience and wisdom. Finally, it means that firms must have the analytical resources and capabilities to discover and link patterns in the data or analytics to company operations.
