3 Things You Need to Know to Master Self-Service BI Apps

While much ado was fabricated near cocky-service business intelligence (BI) apps and democratizing information during the Large Data heyday, one doesn't hear much about any of that now. It's as if all of these things are so routine then 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).

But that'due south not the reality for business analysts and line users throughout the ranks of companies everywhere today. While self-service BI apps have materialized, many yet go out users stuck between a statistical stone and a visualized hard identify. Never fear, help is here!

Crib Canvas Survival Pointers

If you lot can't or don't do math beyond calculating tips equally a percentage of your dinner bill, splitting the bill between multiple diners, or balancing your checking account one time you get home, no worries. In fact, many people can't, or at least don't, do those things without the assist of an awarding. Yous're certainly non lonely in being a flake mystified over stuff such as algorithms, data science, and statistics. And even if y'all 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'southward perfectly okay, too.

The crib notes for those who notice statistics abhorrent or only impenetrable are the same: stick with self-service BI apps that piece of work from natural language queries or that have automated the entire data mining process right downward to the selection of information 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 yous'll detect those limitations detailed in our cocky-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 practise; that's kind of the whole point behind these apps. They're partly automatic virtual assistants to human experts who just want the facts and then they can become blacken the lesser line. So, there! You're off the hook sort of, kind of, maybe. You don't accept to suffer flashbacks to the college horrors of linear algebra and statistics because there are all these apps for that.

Unfortunately, y'all do still demand to empathise how that stuff works at least. If you only cannot force yourself to revisit or refresh your skills in this area, and so 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 primary of on-the-chore data wizardry in your visitor simply don't desire to become all out for the data scientist title, and so accept a quick online course to sharpen your agreement of statistics. Some examples of online education providers for basic and advanced statistics include Khan Academy, Statistics.com, and Udemy.

No, you don't demand a caste in statistics to use self-service BI apps; just having a working knowledge of what the terms hateful and what the concepts are will suffice. Then, even a few podcasts, perhaps such as this series, may exist enough to become you on the right track.

The more you understand nearly statistics, the better off you'll exist. If aught else, you'll better understand what data y'all demand 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 accept much more confidence in the analysis if y'all know what to wait for. "Y'all need to exist confident that the correct processes and controls are in identify to ensure the data is accurate," says Mike Duensing, Chief Technology Officer and Executive Vice president of Applied science at Skuid. "Equally an example, y'all don't want to present a trend to your executive squad that is fresh from your land-of-the-art BI tool, but to find out later it is completely wrong."

The 3 Things You lot Need to Know

Assuming you take already either chosen ane of the AI-driven apps or one of the more than user math-oriented cocky-service BI apps, the following are three things y'all need to know to make the best use of cocky-service BI apps.

ane. Data literacy is a existent thing you lot need to have. Yep, we touched on that earlier in the word of the value of certain math skills. Merely it is of import to also explain what data literacy is and the skills one likely needs to focus on to ameliorate their overall score. "Data literacy is defined past MIT and Emerson Academy 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 information: 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 information: involves filtering, sorting, accumulation, comparison, and performing other such analytic operations on it.

d) Arguing with data: involves using data to support a larger narrative intended to communicate a bulletin to a item audience.

"If at that place's a takeaway from 15 years of working with organizations and data, it's this: Business users love to find stories in their information, and will piece 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'due south interesting into what's actionable. In the same way, l,000 fans at a baseball game love looking at player statistics on the Jumbotron; very few of them have the concern 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 i 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 direction (CRM) data and thus can automatically, via Einstein, predetermine what you lot're going to desire 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 information. Again, the data fix is of a well-defined blazon and the queries are predictable and thus pre-set up.

Not sure where to beginning in shaping your query for a more general-purpose BI app? Usually your company or manufacture'south key performance indicators (KPIs) are a adept starting point as they define analysis already known to be useful. You tin brainstorm layering or calculation related or new questions from there. "KPIs can be single metrics, similar full acquirement, or composite metrics, like acquirement per active user," says Ariel Michaeli, co-founder and CEO of Appfigures. "So it'due south important that the BI platform has the ability to use multiple metrics."

Don't let the "self-service" characterization on these BI apps end you from asking IT or an experienced business analyst for help. "If you can't find a metric that you're looking for, inquire! Information technology'southward possible that it wasn't function 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, then is anticipating the questions likely to come after you present the results of the data analysis because that may prompt you to practise further analysis. "Make sure that you can reply the half-dozen questions people are most likely to ask because they will ask," advises Lucio Daza, Managing director of Technical Production Marketing at AtScale.

Data is the alpha and the omega of the entire exercise

3. Data is the alpha and the omega of the entire practice. A great bargain depends on the information you choose to use. It is the user who chooses, loads, and cleans the data, so yeah, the onus is generally on you. The one-time adage "garbage in, garbage out" all the same applies. As Olivia Duane Adams, Main Client Officer and founding partner of Alteryx, puts information technology: "Understanding your question will bring you lot back to the data itself, like knowing what data is needed and where it might live. Afterward all, data does not create insight until you put it through analysis."

You must recall through the process, from information selection to query germination, before y'all do anything with the app. Otherwise, you're just fishing. Not that data exploration doesn't have its identify. But, if y'all demand specific insights fast, then you ameliorate make certain you're at the right pond and carrying the right allurement before you cast the offset line. Remember that you lot are the subject matter expert (SME), not the motorcar. Use your talent and experience to figure out what data you need and to hammer it into prime number shape before telling the software to do the belittling work.

So, what do y'all practise if you totally stone 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 evidence you how to get started since the barrier to learning is so much lower than traditional BI products."