"Too Much Information" was the name of a famous 1993 pop song by the band Duran Duran. The song was a scathing commentary on the crass commercialism of music at the expense of artistic appreciation by the consumer.
However, that song's title is also an apt description of the data overload burden that most 21st businesses have to contend with.
And what most businesses fail to appreciate is that data can be a blessing and a curse. Of course, data must be analyzed and assessed for profit and market advantage. In the 21st century, there is always too much information to quantify and this is a problem that will only get progressively worse in the future.
But some forms of data are more useful than others. And it can be counterintuitive for businesses to rely solely on the IT office interpreted data instead of having its relevant employees interpret it.
The rise of self-service analytics could be the solution to this problem. But before we dive into self-service analytics and its continuing rise in the business world, let's examine the problems it can solve.
Data is time-sensitive – the longer you store and analyze it, the less it becomes relevant to your business needs market-wise.
Also, most companies and their IT teams or quantitative analysts only successfully use and implement a minuscule percentage of all the data they ever collect to benefit their employers.
The more data your business collects, the more time and work hours your business must sacrifice to scrutinize that data. It costs money to collect data, store it, pay for the energy costs to store and process it, and then implement it in the business market in a regulation-compliant manner.
There is just too much information in the world for most business IT teams to contend with.
There was a 4,300% increase in the amount of data produced in the world relative to businesses' needs in 2020.
And even when an IT team successfully synthesizes a lot of data, it takes time for them to crystallize it. Then, IT teams pass along their interpretation of data to various departments that have to make sense of it independently.
And the systemic coordination between IT teams and their colleagues is becoming more challenging in the post-COVID-19 business world. Over 57% of IT workers now work remotely from home offices.
If you need help with data self-service analytics and data mapping, contact Zuar today.
Self-Service Analytics 101
Self-service analytics is a relatively simplified business intelligence software version of IT or quantitative analysis of market-relevant data. Businesses can use self-service analytics to cherry-pick, streamline, and analyze data in a straightforward, layperson manner.
Self-service analytics allows business professionals to generate reports and records based on business data they can assess themselves with minimal reliance on IT teams or quantitative analysts.
Self-service analytics is a kind of simplified business intelligence software that empowers users to make reports, charts, graphs, layouts, and more, based on data that is usually sourced out for interpretation by information analysis teams.
When you use self-service analytics software, your business can better understand data relevant to your business needs.
You can decipher data on your own to better understand your business operating metrics, business model, and how to course-correct if necessary.
Most importantly, you can interactively use time-sensitive data at the moment for your business' benefit instead of waiting for that data to become irrelevant by the time an IT team or quantitative analyst synthesizes it.
Now that we have explained self-service analytics let's clarify the benefits.
Self-Service Analytics Software is User Friendly
Relative to coordinating with an IT office or quantitative analyst and then struggling to comprehend their complicated reports, self-service analytics is extremely user friendly.
With self-service analytics, you can learn to create reports or modify existing reports using data yourself instead of relying on other offices.
You may think that if you are used to receiving voluminous, complicated, and hard to decipher data from IT team and quantitative analysts, then how can you do it on your own with self-service analytics?
Over 70% of successful self-service analytics users are first-time and novice users with no prior experience using such software. For context, only about 5% of self-service analytics users are professional business analysts.
Less Reliance on IT Team Interpretation of Data
It should not be assumed that IT teams or quantitative analysts are bad for business or unnecessary. They perform important functions for business and have to contend with incredible amounts of data.
Self-service analytics frees up IT teams and quantitative analytics to focus on the information they need to deal with.
Data collection, analysis, and input are streamlined with self-service analytics. Businesses don't need to contend with the delays, turnaround bottlenecks, and lengthy interpretations of their own data by others when they use self-service analytics.
Better Protection of Business Operating Data
Businesses are the victims of massive, industrial-scale cyberattack data breaches every year. Every year, sensitive business data is stolen, and the personal data of hundreds of millions of Americans becomes compromised.
Businesses that are compromised by cyberattacks lose money and suffer damage to their PR brand.
What does that have to do with self-service analytics?
When you use self-service analytics, you are empowered to analyze your most time-sensitive and business operations data on your own.
Most importantly, you can source out less business-sensitive data to IT teams, quantitative analysts, and outside vendors.
Business data breaches and theft are not always taken in Mission: Impossible super-hacker fashion. Business given to unprofessional sources or worse, sources who accidentally share it.
The Future of Business is Self-Service Analytics
There is extremely too much information in the business world that can be collected and analyzed for your business' needs in a timely fashion.
The rise of self-service analytics is now, and your business should get ahead of the curve as soon as possible.
Need help with your business data analytics? Contact Zuartoday.