Strong data analysis is now an essential part of executive reporting. It is also central to the value that architects and digital strategy managers offer the business.
The most effective enterprise analytics are tailored precisely to your specific business and technology environment.
“Corporate leaders must expand their analytical range from monitoring and control (operational analytics) to forecasting and planning (strategic analytics)”
– MIT Sloan Management Review
Ideally, calculations are also transparent and easy to adjust as needed. We live in a world where the algorithms on which decisions are based are too often hidden from view. Metrics which are transparent are more trustworthy and much more practical.
Taking advantage of low-code & no-code
Many of us will be familiar with the move to low-code and no-code development platforms, which offer a visual step-by-step, drag-and-drop way for businesses to build apps.
Even more will have seen block-based coding platforms: kids are learning to assemble and tweak instructions for a game or animation using apps such as “Scratch” from MIT (even if most of them use this knowledge to hack games to avoid losing “lives” – endless fun!)
For architects and business leaders who need to set up quantitative analytics to build an understanding of their chosen enterprise metrics, algorithms can be used to do the heavy lifting of both business and technical analysis.
ABACUS now offers a no-code Visual Algorithm Composer: a block-based workflow which allows EAs to assemble calculations from across their data and architectures and to tailor their analytics as they map out scenario options.
What enterprise analytics can I calculate using algorithms?
What metrics matter to your business? Each enterprise needs to decide on a set of numbers which guide decision making, specific to its datasets, its goals, projects, requirements and risks.
Use algorithms to set up the calculations you need to track the health of these projects and roadmaps in real-time.
Broadly, a standard set of enterprise analytics architects and digital strategy managers might set up include:
- Financial analytics (Cost, TCO, ROI, NPV etc.). These can be used to:
- Weigh up cloud migration options and recommendations
- Calculate Total Cost of Ownership (TCO)
- Aggregate budgets and project financials
- Automate your cost attribution calculations
- Risk, Security and Maturity metrics etc. to identify risks and threats and map out scenarios and strategies to avoid them
- Monitoring technical metrics with analytics for Performance, Reliability, Complexity, Openness, Modularity, Cloud Readiness, Resource Utilization, Response Times, Availability
- Check the number of applications by department
- Understand Process end of life dates from technology lifecycles
You can also set up algorithms which allow you to keep an eye on trends in key business and IT metrics.
How to Build Your Own Algorithms
Just like other block-based coding platforms, the first step in setting up an algorithm involves using a set of building blocks to describe a calculation. Start with something simple, such as a “sum” algorithm which adds the values in two columns and presents the results of the calculation in a third.
More complex algorithms may involve other operations including:
- Add, Subtract, Multiply, Divide
- Min, Max, Average, Count
- Power, Log, Atan
Users can set properties on each “block” in the Algorithm Composer. Select operations to
- Aggregate multiple data qualities
- Vary data processing order
- Attribute values across various data types
- Measure impacts on projects based on dependency limitations
With experience, users can pull together an algorithm workflow in a matter of minutes. It’s also possible to adjust algorithms, import and modify a pre-built algorithm, or export an algorithm to XML so it can be run across other projects.
Who can build or edit algorithms
A big advantage of using a no-code platform for setting up analytics is that users from across the business can get involved and learn to set up algorithm workflows themselves. No experience of coding is required, just an understanding of what information the department or managers need.
Users might be:
- Enterprise Architects, Solution Architects and other Architecture team members
- Data Scientists
- Digital Transformation specialists
- Business Strategy managers
- Data owners or department heads
Graph Database Analysis: Real-Time Reporting
Gartner has recently identified graph databases as a “Top 10 Data and Analytics Technology Trends for 2019”:
“The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.”
The ABACUS toolset has used graph database technology for over 15 years, and it’s a key enabler of algorithm-based analytics.
Having a graph database behind the scenes provides real advantages: users enjoy faster processing times and graph databases are ideal for capturing and navigating complex information and relationships. They give organizations greater ability to move analysis and reporting into a real-time or near-real-time mode.
If you’d like to test drive ABACUS Visual Algorithm Composer, you can download a free 30-day trial today and follow the tutorials and videos in our ABACUS Community