Big data analytics has a major role to play when it comes to provide adequate data driven insights to the CEO. Conversely, it gives employees access to information that helps them perform more efficiently. Advance Big data Analytics solutions like Bizintel360 make the task of collection, storage and ultimately projection of data through visualization a much easier and significantly faster process.

Primary business roles and essential insights for the CEO:

Finance:
CEO gets a real- time visibility into company finances that help him mitigate unforeseen situations and handle risk better

IT:
CEO can measure the cost of service delivery, time to resolution of a support ticket and evaluate the need to hire more resources or allocate tasks to existing employees

HR:
In-Depth Analysis of your Human capital is essential information for the CEO. Employees make or break an organization. Big data analytics help identify the effectiveness of HR in building and retaining resources in a company.

Marketing:
CMOs and CEOs have the analysis of the various marketing activities at hand to help them allocate budget, resources and time to a profit-making venture and discontinue non-productive ventures.

Sales:
CEOs have all the data to judge a sales rep’s performance, predict deals, pipeline development, and team performance to understand the challenges and sales best practices.

BizIntel360, a truly self-service big data analytics solution that combines the advantages of the cloud with the advanced capabilities of today’s data warehousing and visualization solutions. BizIntel360 is ideal for all organizations that want to leverage the power of big data without stretching their resources. BizIntel360 can scale to meet any organization’s needs. We built our solution to allow companies of all sizes to harness the power of advanced data collection, analytics, and visualization quickly. In fact, you can pull data from any data source—structured or unstructured—within hours of setting up your account. You don’t need expensive extraction, transformation, and loading (ETL) tools, bottomless IT resources, or large-scale data warehouses to put big data analytics to work.