eMagiz currently sees two major trends in the ICT field where we sees a clear role for our platform. The first major trend is the huge amount of data coming into Enterprise ICT architectures, for which the often traditional architectures are insufficiently equipped. The second is the need to facilitate real-time decision making directly from these immense data streams.
Suppose you get sensor data every second about the status of a particular operation in one of your processes. You don't want to store all that data, but you do want to get a signal when there is a deviation in that status from the norms in that process. By temporarily holding sensor or other data, enriching and aggregating it, you can extract such new insights from your data streams. You could think of this as a kind of "edge computing" for data streams. With eMagiz State Generation we are opening new doors for our customers and partners in the field of real-time decision making.
How does State Generation work?
In a 'traditional' IT environment, you have to go through quite a few steps to gain insight into what is happening within the data streams entering your Enterprise landscape. From the data sources, you go through a datalake from which you fill a datawarehouse by means of an ETL process. Using BI, AI, Big Data or machine learning, you can then gain insights into trends, anomalies, dependencies or results within your data streams. If you have these insights, eMagiz offers you the following possibilities with State Generation:
Enrich data based on other data present within the Enterprise environment. For example:data = 18, enrichment is: degrees celsius in room X of building Y at 16:15.
Look at the data as a whole and determine average values, minimum and maximum. For example: average increase per 15 minutes of temperature in room X of building Y is 1.5 degrees Celsius.
Detect and send notifications as soon as state changes are detected. For example: if average temperature increases by more than 1 degree celsius in 15 minutes, turn top cooling up one level.
The above example is a simple one but State Generation allows organizations to apply even particularly complex insights in real-time to all data streams pattern-independent (messaging, API, event-streaming or hybrid) within the landscape.
Learn more about State Generation
For Dutch IT Channel's talk show, Bart (Commercial Manager) & Mark (Product Owner) were interviewed by Danny Frietman about how the trends of growing data streams and real-time decision making are impacting companies and how a concept like State Generation can help.
Watch and learn more about the application of State Generation in 10 minutes. To get access to the talk show of Dutch IT Channel please fill out the following form.