A tiger in the bathroom. A baby. A missing tooth. The groom is gone! These were just some of the surprises that the wolf pack woke up to in the movie “The Hangover.

The guys figure that if they can just piece together what happened the night before, then they can find the groom and get him to his wedding in time. Of course as they start to look into this, they just uncover more and more things that happened that they weren’t aware of, further complicating their situation.

Sound familiar?

This is a lot like what it can feel like in managing data-driven organizations. No, data analysts aren’t getting dead drunk, blacking out and finding a chicken running around their office, but they may see that their smoothly functioning operations has been thrown for a loop by some glitch or missed business incident.

Big Data Hangover

Source: IMDB

All they can say is ‘what happened?’, just like in the movie! OK, not quite like in the movie, but in the same spirit, ok, you know what I mean. Data analysts end up spending a lot of time investigating issues that are hidden within the vast volume of data and events, and often don’t know what to look for.

What’s the Big Idea in Big Data and Business Intelligence

Data volumes are exploding. We are now in a data-driven economy where no organization can survive without analyzing the activity within their data for trends. Whether it is a fintech service or an ecommerce site, wrangling data has become a crucial job to be done before taking a single step further.

This can leave managers struggling to keep up with the myriad of business intelligence-related reports from traditional business intelligence tools  – which fail to effectively and efficiently analyze and interpret the data in a timely manner. Traditional Business Intelligence approaches are just not suited for this Big Data world. You can’t just throw more dashboards or reports at this challenge.

Data analysts need agile solutions that can outsmart “unpredictable” changes at the right time, to minimize the damage that surprises could potentially do to customer experience and ultimately to the business.

Obstacles In Bringing Intelligence To BI

That hazy, groggy feeling from a hangover, with little recollection of what happened before is kind of how you may feel trying to make sense of data to find new opportunities. The difference from the movie is that, in the movie the guys just had to follow a linear trail of clues leading from one crazy situation to the next, while in business intelligence you might not even have a clue. When performance slows or an under the radar business incident occurs, you can face millions of data points, leaving you to sift through them to figure out what was impacted and where.

So, one of the key obstacles in bringing the actual intelligence to BI is being able to properly interpret the vast store of data correctly – harvesting the pertinent business “stories.” An end user trying to understand what happened, or more likely what went wrong, would need to know the context of their data to correlate with relevant events.

Do You Make Spending Surprises?

Did you ever make a business decision without all the facts? Decisions are sometimes made without considering all the data, or with what is often described as going with a gut feeling. You cannot simply rely on instinct when making decisions. While most of the existing BI solutions can process and store a huge amount of data with many dimensions, they don’t offer an easy way to get real-time business insights from the enormous amount of data they collect.  Traditional BI tools lack detailed analysis to the most granular level of detail, with no correlation, and do not offer any real-time actionable insights, leaving teams arguing about who to blame, instead of having meaningful business conversations.

Data analysts simply can’t keep up trying to crunch larger and larger datasets to find ways for the business to improve its key KPIs and avoid surprises.

Don’t Allow Surprises To Surprise You

The way we manage unexpected events could result in the ultimate success or failure of the business. Thus, learning how to effectively tackle surprises is critical in the data driven world we work in. There are always surprises when you work with data, with most streaming and in motion.

The most fundamental thing to understand about managing surprises is to expect the unexpected. It could be a simple pricing error, negative sentiment on social media, a server glitch that slows load time, or an error in the payment gateway that makes checkout impossible. Anyway, the responsibility to handle surprises can be entirely manageable.

Meaningful Business Insights

Well you probably aren’t in Vegas with a friend about to get married, nevertheless you don’t have time for the tiresome effort of checking reports and dashboards while risks loom around the business. You need to be ready for surprises and get to bottom of issues – fast. If we were talking about a real hangover, then the solution would probably be some pretty strong coffee.

For our business reality, that strong coffee needs to able to convert raw data from varied sources into a cohesive, concise picture of business problems. With traditional BI solutions affected by the dynamics of people, processes and authorities, you need to take into account a wide variety of data sources. A meaningful AI-powered analytics solution can help you identify actionable business insights, rather than generating more dashboards and reports to review. Highly scalable machine learning-based algorithms that can learn the normal pattern of any number of data points and correlate different signals to accurately identify anomalies (surprises!) that require immediate action or investigation.

Even with a great strategy you may still face surprises with your data, and lie awake at night wondering what new event, omission or update will blind side you tomorrow morning.


Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

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