Business intelligence has evolved past the point when it was just regarded as essential but not exactly a primary driver of enterprises. And, obviously, we have the big data explosion to thank for that transition. Analytics, at least in its advanced form, no longer limited itself to the analysts, as experts put it.
The field grew substantially in the past year, so it won’t be surprising if its momentum carries over to 2021. Indeed, there couldn’t be a better example of a landscape that’s currently metamorphosing before our very eyes than the one business intelligence flourishes in. Let’s take a closer look at the 5 Business Intelligence trends that are, more or less, responsible for this ongoing, dynamic transformation.
All Aboard the Mobile BI Train
The pandemic saw to it that the conventional business model would become, at best, obsolete next to the perks offered by mobile solutions and e-commerce as a whole. The necessity of social distancing basically sealed its fate. That said, we can only expect this situation to be favorable for mobile business intelligence trends.
Users would pretty much want to be able to access their data any time and anywhere, and no other platform can deliver this kind of convenience than mobile devices. Currently, there’s still a marked shortage of solutions for this, but with the expected surge in demand for them, don’t be surprised if plenty of companies pivot toward coming up with their original mobile BI offerings.
Real-time data, 24/7 access, and collaborating anywhere are but some of the guaranteed benefits of these solutions. Even collaborative business intelligence already falls under this umbrella. As if the mobile field could not become more relevant, right?
Keeping Data Relevant Through DQM
In business intelligence, it’s not so much the quantity of data that you acquire than its relevance and accuracy. You may acquire data on a consistent basis, but how much of it is ever really relevant to your industry or chosen niche? BI’s full potential can only be unlocked if it’s fueled by the right kind of data in short.
The solution to this? Data quality management. More often than not, enterprises go about with this by setting up an entire framework of tools and individuals asked with the acquisition of precise and hyper-relevant data. Essentially, it’s all about going for quality over quantity, and as most success stories have proven, this is the way to go forward in most cases.
Reinforcing Data Security
Keeping data secure has been a priority for years now. However, with the significant rise in data-driven enterprises worldwide, it’s becoming harder to stay ahead of risks and vulnerabilities. It’s not so much the larger scope as the volume of personal information that businesses have to secure in order to maintain public trust and reduce hacking incidents.
Otherwise, business intelligence will have a harder time helping businesses that rely on it to keep their market value up. This trend is practically inevitable as more privacy regulations like the EU’s GDRP and the US’s CCPA are now in place. Of course, such regulations, while they do lend themselves boosting security, are not without their downsides.
Most, like the Data Privacy Shield, only make life harder for software companies, for example. What’s sure s that companies will only be increasing their investments into tools, services, and platforms that will boost data security. And this is even with the pandemic’s effect considered. Understandably, digital business is fairly young and rife with risks, but this trend serves as a promising sign that companies continually take active steps to curb them.
Storytelling Guided by Data
Data analysis will always be fundamentally connected to business intelligence. Nonetheless, gone are the days when it’s limited to just conveying information. Now, analysts are adopting storytelling to make the data not only more engaging but accessible as well.
One undeniable advantage of this is that it often allows businesses to come up with practical answers to lingering problems. There’s also a clear focus on personalization this way, which is only the ideal way of sharing data. Using data to tell stories makes it easier to inspire new ideas among business owners, and without a doubt, it also allows them to make better decisions in the long run. But, at the heart of it, all are two things: better personalization and engagement.
Artificial Intelligence as a Necessary Catalyst to Achieve Greater Data-Driven Leaps
Last but not least is the continuing impact of artificial intelligence in its. With the proven immense improvements done by the personalization and customization perks of AI in various fields, it’s not surprising that the same boon is being enjoyed by business intelligence.
AI and BI form an inevitable tandem since both play equally crucial and varying roles in the digital landscape. With AI-powered business intelligence, access to real-time data not only became viable but became the most preferred by businesses. AI also allows businesses to respond to any type of problem-related to data with unprecedented velocity.
The same can be said for the amount of effort that AI saves when it comes to analyzing datasets. Certain example scenarios include simply assigning the data source that should be analyzed by the algorithm. And from there, you can already gain access to what-if scenarios, trends, key segments, and issues.
With AI, it’s not just about automation and convenience, but having a stronger grasp of the data that is available to you. Its advantages even extend to heightening security and predictive analytics, making it no less than an all-prevailing trend that will continue to run its course past 2021.
As is only proper in a field that’s undergoing rapid evolution, staying on top of relevant business intelligence trends in 2021 will only pay off for most businesses and solution-providers in these unusual but not less interesting times. These trends also serve to prove that business will go on and the majority of its continuous growth is all thanks to presently available technologies as well as the timely response of data analysts and enterprises to today’s crises.