While much ado was made about self-service business intelligence (BI) apps and democratizing data during the Big Data heyday, one doesn't hear much about any of that now. It's as if all of these things are so routine and so deeply ingrained in the daily work grind that further discussion is no longer needed. The buzz has faded and the world, it seems, has moved on to fancier, fantastical things such as machine learning (ML) and deep learning and all things artificial intelligence (AI).
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But that's not the reality for business analysts and line users throughout the ranks of companies everywhere today. While self-service BI apps have materialized, many still leave users stuck between a statistical rock and a visualized hard place. Never fear, help is here!
Crib Sheet Survival Pointers
If you can't or don't do math beyond calculating tips as a percentage of your dinner bill, splitting the bill between multiple diners, or balancing your checking account once you get home, no worries. In fact, many people can't, or at least don't, do those things without the help of an application. You're certainly not alone in being a bit mystified over stuff such as algorithms, data science, and statistics. And even if you aren't baffled by any of those things, maybe you just don't want to do them. Not everyone considers that to be fun and that's perfectly okay, too.
The crib notes for those who find statistics abhorrent or simply impenetrable are the same: stick with self-service BI apps that work from natural language queries or that have automated the entire data mining process right down to the selection of data visualizations. Such apps include IBM Watson Analytics and Salesforce Einstein Analytics, respectively. And, why yes, both are AI-driven.
Apps such as these have their limitations, too, and you'll find those limitations detailed in our self-service BI tools and data visualization tools review roundups. But even with their drawbacks, they are perfect tools for the mathematically challenged and those seemingly allergic to statistics.
Don't Self-Service BI Apps Do the Math?
Why, yes, they do; that's kind of the whole point behind these apps. They're partly automated virtual assistants to human experts who just want the facts so they can go blacken the bottom line. So, there! You're off the hook sort of, kind of, maybe. You don't have to suffer flashbacks to the college horrors of linear algebra and statistics because there are all these apps for that.
Unfortunately, you do still need to understand how that stuff works at least. If you simply cannot force yourself to revisit or refresh your skills in this area, then refer to the crib notes above.
If you'd rather be the most wanted talent in your field, the hottest hotshot on the team, and the master of on-the-job data wizardry in your company but don't want to go all out for the data scientist title, then take a quick online course to sharpen your understanding of statistics. Some examples of online education providers for basic and advanced statistics include Khan Academy, Statistics.com, and Udemy.
No, you don't need a degree in statistics to use self-service BI apps; just having a working knowledge of what the terms mean and what the concepts are will suffice. So, even a few podcasts, perhaps such as this series, may be enough to get you on the right track.
The more you understand about statistics, the better off you'll be. If nothing else, you'll better understand what data you need to use, why you need to toss outliers, what data to assign to which axis when plotting a chart, and how to shape a useful query. You'll also have much more confidence in the analysis if you know what to look for. "You need to be confident that the right processes and controls are in place to ensure the data is accurate," says Mike Duensing, Chief Technology Officer and Executive Vice president of Engineering at Skuid. "As an example, you don't want to present a trend to your executive team that is fresh from your state-of-the-art BI tool, only to find out later it is completely wrong."
The 3 Things You Need to Know
Assuming you have already either chosen one of the AI-driven apps or one of the more user math-oriented self-service BI apps, the following are three things you need to know to make the best use of self-service BI apps.
1. Data literacy is a real thing you need to have. Yes, we touched on that earlier in the discussion of the value of certain math skills. But it is important to also explain what data literacy is and the skills one likely needs to focus on to improve their overall score. "Data literacy is defined by MIT and Emerson University as the ability to read, work, analyze, and argue with data," points out James Fisher, Vice President of Global Product Marketing at Qlik . Below he explains each ability:
a) Reading data: involves understanding what data is and what aspects of the world it represents.
b) Working with data: involves creating, acquiring, cleaning, and managing it.
c) Analyzing data: involves filtering, sorting, aggregating, comparing, and performing other such analytic operations on it.
d) Arguing with data: involves using data to support a larger narrative intended to communicate a message to a particular audience.
"If there's a takeaway from 15 years of working with organizations and data, it's this: Business users love to find stories in their data, and will slice and dice endlessly to get them," says Adam Nathan, founder and CEO of Brainbox Consulting, which recently sold to Logic20/20. "Where they struggle is translating what's interesting into what's actionable. In the same way, 50,000 fans at a baseball game love looking at player statistics on the Jumbotron; very few of them have the business chops to play Moneyball."
2. The right questions are everything. Self-service BI apps are partially automated app assistants. This means that, normally, you're the one who must think of the question (aka, the query). Forming that query is very important because the answer is only as useful as the question. One exception to this rule are specialty apps such as the aforementioned Salesforce Einstein Analytics, which focuses on sales and customer relationship management (CRM) data and thus can automatically, via Einstein, predetermine what you're going to want to know from your sales and customer data. Another example of a specialty BI app is Google Analytics with its focus on website and mobile data. Again, the data set is of a well-defined type and the queries are predictable and thus pre-set.
Not sure where to start in shaping your query for a more general-purpose BI app? Usually your company or industry's key performance indicators (KPIs) are a good starting point as they define analysis already known to be useful. You can begin layering or adding related or new questions from there. "KPIs can be single metrics, like total revenue, or composite metrics, like revenue per active user," says Ariel Michaeli, co-founder and CEO of Appfigures. "So it's important that the BI platform has the ability to use multiple metrics."
Don't let the "self-service" label on these BI apps stop you from asking IT or an experienced business analyst for help. "If you can't find a metric that you're looking for, ask! It's possible that it wasn't part of the initial rollout of your BI solution," said Doug Bordonaro, Chief Data Evangelist at ThoughtSpot. "An analyst might be happy to add it quickly for you."
And, while crafting the query you'll use is crucial, so is anticipating the questions likely to come after you present the results of the data analysis because that may prompt you to do further analysis. "Make sure that you can answer the six questions people are most likely to ask because they will ask," advises Lucio Daza, Director of Technical Product Marketing at AtScale.
3. Data is the alpha and the omega of the entire exercise. A great deal depends on the data you choose to use. It is the user who chooses, loads, and cleans the data, so yeah, the onus is mostly on you. The old adage "garbage in, garbage out" still applies. As Olivia Duane Adams, Chief Customer Officer and founding partner of Alteryx, puts it: "Understanding your question will bring you back to the data itself, like knowing what data is needed and where it might live. After all, data does not create insight until you put it through analysis."
You must think through the process, from data selection to query formation, before you do anything with the app. Otherwise, you're just fishing. Not that data exploration doesn't have its place. But, if you need specific insights fast, then you better make sure you're at the right pond and carrying the right bait before you cast the first line. Remember that you are the subject matter expert (SME), not the machine. Use your talent and experience to figure out what data you need and to hammer it into prime shape before telling the software to do the analytical work.
So, what do you do if you totally rock as a SME but are also a completely lost novice at selecting data and using a self-service BI app? "Get to know your local power user," says ThoughtSpot's Bordonaro. "Chances are, there's someone sitting very close to you who can show you how to get started since the barrier to learning is so much lower than traditional BI products."