Archives: February 2017
In a recently completed survey of non-customers, we found that analysts who used Query/400 reported spending an average of 1.625 hours per day extracting, manipulating, and distributing data. We know from previous studies that people who move to NGS-IQ typically cut the time they spend on these tasks by approximately 50%.
That reduction in time is due to NGS-IQ having many more features which let analysts and business users write and run fewer queries and automate data transfers, spreadsheet updates, and report distribution. The math works out to 0.8125 hours per day in labor savings or about 10% of an eight-hour work day. Using a national average of $70,000 annual salary for a business analyst, the financial savings equate to $7,000 per year.
This productivity savings doesn't include the intangible business value and impression you make on your customers when staff members regularly have meaningful, accurate, timely data at hand.
While it’s unlikely that many companies will store their IoT device messages in the IBM i environment, it's easy to imagine most IBM i customers having systems (maybe cloud based) that store IoT message streams alongside their DB2 on i/ERP database.
While the data is stored separately, there is value to be realized from “merging” IoT and ERP data. Think about sensor data (IoT data) captured from products being used by thousands of customers. This data, once parsed and placed into a searchable format, needs to be viewed in different ways – by product, by customer, by order or install date, and so on. That product, customer, and order information is in the ERP database. Business people need this combination of data to give meaning and perspective to the IoT data.
Depending on the format and volume of your IoT data, with a little data cleansing and filtering, you could probably upload extracts of IoT data to DB2 on i. Once the extracted IoT data is there, forward thinking IBM i customers can begin to discover its business value.
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