Data analytics makes the numbers you need tangible, understandable, and actionable. Axians defines IT data analytics as the process of transforming data into decision-making when businesses retrieve, cleanse, combine, interact, visualize, and act on information to support new insight discovery. Through regular analysis, organizations are better positioned to reduce risk; identify oversights, gaps, and opportunities; make more mature business decisions; and implement real departmental and enterprise-wide improvements.
We work with you to set measurable program goals to reduce manual reporting, improve the speed and accuracy of key information retrieval, and boost your team’s satisfaction with the results. Axians defines the key roles at your organization who have a hand in data operations, reviews program oversight and governance, ensures business alignment, organizes process collection and prioritization, and determines the best methods of supporting your team through program use and ROI.
Axians reviews your data systems in place, looking at legacy sources, data warehouses, and data lakes to cleanse information, improve business intelligence, support historical data use for trends and predictions, and prevent data hoarding and redundancy.
Axians establishes a formal testing procedure around your data and dashboard development to ensure the most effective and consistent view of your program possible and integrate new systems seamlessly. Our dashboard program defines your strategy and creates a single access point to data analytics, designs a data visualization interface that fits your branding and use preferences, brings in the right team members for refinement, and sets out to develop and test a tool that sets up your business for data success.
With our continuous service improvement (CSI) mindset, Axians keeps your business focused on future enhancements, helping your data analytics dashboards stay relevant and insightful. We regularly assess your current data situation to pinpoint new needs, establish fresh goals to reduce data redundancy and improve information accuracy, monitor your progress and support business decisions, and optimize efforts with reporting and new features and data sets.