Enterprise organizations create, consume, process, and channel a lot of data. Agreeing on that means we also agree that today, every company is a software company as technology permeates throughout every layer of modern business.
ASUG members in every industry vertical will know this reality all too well. But with SAP database technologies (as well as other vendor deployments) running at the heart of their operations, are all members looking to surface those data streams in ways that could allow both technical and nontechnical employees to interact with data more effectively?
If it weren’t obvious, we’re talking about data visualization. And the answer is yes, because data now makes the world go round.
Data Visualization Defined
For want of a formal definition, we can say that data visualization is the use of graphs, diagrams, charts, and other visual representations such as heat maps to provide a means of understanding trends, outliers, anomalies, and patterns in data. Data visualization provides a means of understanding the movement of data trends by showing where defined classified groups of data are moving by using different graphical shapes, colors, and sizes.
That’s a very textbook definition, but it does help to illustrate what a typical data visualization looks like. ASUG members using these tools might, for example, plug in sales by region, growth by department, employee turnover by age group, or some other classification of data analytics for representation in a data visualization tool.
SAP does provide a degree of technology in this space in the shape of the SAP Analytics Cloud service. This business intelligence technology can generate reports and offers an import/export feature for your spreadsheets and visuals. But this is not necessarily core SAP territory. For that reason, we find that SAP is keen to integrate openly with many of the usual suspects in this space who have developed more dedicated data visualization solutions. Key players include: Tibco Spotfire, Sisense, IBM Watson Analytics, Microsoft Power BI, and (now acquired by Salesforce.com) Tableau. For wider reference, you can view Gartner’s Magic Quadrant for Analytics and Business Intelligence platforms 2019.
Delineating Data Visualization
When used effectively, good data visualization can offer organizations a representation of real-world business actions, transactions, and processes in graphical form.
But even when using the dedicated software tools in this space, there are limits to functionality. What data visualization doesn’t do is provide a means of controlling business actions from the graphical representations themselves. It’s not a steering/driving business dashboard in that sense.
What users can do inside any given data visualization is to ask deeper questions of the datasets presented. If you asked for a visualization of sales by region and then by year, you would typically have the option of going into more granular detail and getting sales by region and then by month, and so on.
Democratizing Data Visualization
Data visualization evangelists talk about the need to democratize the use of these tools. They think that practically every employee in every business has the potential to execute some form of analytics over their work domain and look for ways to improve workflows and business processes. This drive for democratization takes us toward what the industry likes to call citizen data scientists—where the user touches some form of data visualization.
To make this possible, vendors in this space are working to provide natural language understanding (NLU) to the query engines that users will interact with. This way, users won’t have to program the analytics calculation. Instead, they’ll be able to just ask the software a question in a Google-like intuitive search kind of way.
If we allow this functionality into the business, then we need to make sure that we have both safeguards on who can analyze what through information access policy control and analytics provenance reports to tell us which staff members have used which information resources to create which potential business decisions.
This concern has been reflected in the ASUG report, “The State of Business Intelligence and Analytics,” which noted, “The biggest pain point for SAP customers is data governance (e.g., quality, security, and consolidation). SAP customers recognize that it’s a prerequisite to increased efficiencies and innovation, but most struggle to get it right.” The report further notes that companies struggle with the amount of data they have and how to understand which numbers are accurate. The ASUG analysis found that it is not uncommon for two executives to bring different statistics to a meeting, even though they’re from the same data source.
Lessons Going Forward
Going forward, ASUG members face two key challenges in this space: data source and vendor source.
The data source challenge is a question of whether members have the right level of data stewardship overseeing back-end systems to embrace the use of data visualization at the upper level. This challenge is further compounded by the need to shoulder the complex extract, transform, and load (ETL) operations needed to be able to feed data visualization tools with enough timely data. In a world where real-time information is coming to the fore, making business decisions based on historically archived datasets is not very productive.
The second challenge here is vendor source. In other words, do ASUG members opt for SAP BI technologies or adopt more specialized tools? The issue is highlighted in the ASUG State of Business Intelligence and Analytics report, saying, “With the number of BI tools available, it’s tough to balance agility and speed with the integration needs of major workloads. SAP customers ask themselves: Do I use SAP tools because they better integrate with my back-end systems, or do I choose something that may work better and faster for my business, and then face challenges connecting the output to the data?”
ASUG recommends that as many members now plan to increase their investments in BI, it’s important for companies to prioritize the benefits and KPIs needed from analytics reports to help select the right tools. Data visualization is drawing more interest all the time—it could be time to map your approach out soon.
Register for the ASUG on-demand webcast, “BI: The Good, the Bad, and the Ugly: Planning for Deployment of SAP Analytics Cloud.” To hear how to address some of the trends and pressures that surfaced in the ASUG report on business intelligence, join us March 9–11 in Atlanta for the BI+Analytics Conference.