Charts and interactive dashboards are an essential part of business and market improvement based on real-time data. Charts are basically graphical representation of tabulated data. Visualization is a very effective way to illustrate the results of analysis and is an integral part of any report or presentation. Business or enterprise data can be interpreted visually through interactive charts using visualization tools like Tableau, QlikSense or Power BI.
The Alpha Analytics Visualization teams have wide experience in charting market research and enterprise data using PowerPoint, Excel, .Key (for iOS devices). Interactive real time dashboards are created using Tableau, QlikSense or PowerBI for our clients to illustrate actionable insights. Both static and live views of data can be created by connecting to static data files or live database connections. The various databases we normally connect to could include MS SQL, MySQL, Oracle, SAS, Salesforce, Amazon AWS, Marketo, Hadoop, TeraData etc.; NoSQL databases like MongoDB or even standard inputs like excel or CSV files.
The charting or visualizations could be in any of the buckets:
|Static Data||Live Data|
Frequently Asked Question (FAQs):
- Forecasting of Revenue generated – In this plot estimation of revenue is forecasted for all three locations Mumbai, Hyderabad. Bangalore.
- State Viz Performance- In this plot, we can view and analyse performance of each of the entity in geographic notation, The plot is interactive, once however on the bubble, it reveals other information such as # of claims made, revenue of each of the entity in terms of number and percentage.
3. Growth per Year- In this plot, we can see the growth of organization over the period of time in terms of revenue and payment made.
- Employee Performance- Here top 10 employees performance we are visualized with respect to different regions, policy type and the incentives they are getting.
(All are related and linked to each other dynamically)
Claims Report indicates everything about claims status, delaying in days to settle claim, impact of disease on gender, age group and The policies taken.
1.Claim Status over the previous period- Here claim Status w.r.t. Months and year we are show casing, from this we get to know how many no of claims are settled, rejected, closed and so on
2. Claim Vs Average Delay in Days- In this we are calculating the average no days which is delay to settle claim and count of policies in that particular month.