en
en
Back

Three Major Pitfalls of Big Data That Can Seriously Hurt Your Business

Business - 23rd September 2019
By Marek Hasa

“Crunching the big numbers will always point us in the right direction, right?” No, not really. Capitalizing on Big Data indeed yields very interesting potential in many fields. Nonetheless, the Big Data boom has led many companies to delving into this practice rather blindly, doing all sorts of mistakes on the way. Sloppy data collection and analysis routine often results in poor decision-making of the management, thus hurting the business and eventually also its customers. Let’s take a look at three major DON’Ts which you should definitely avoid in order to successfully implement data analytics and insights into your digital product and business model.

1. The Illusion of Utmost Authority

People tend to trust data-based insights more than anything. And that’s not necessarily a bad thing. On the contrary, we should celebrate the fact that managers gradually switched from inspecting small sample sizes to working with large piles of data. Unfortunately, like any other science, data science can be conducted hastily or with low quality data. Even if the methodology itself is fine, the data set will have its inherent inaccuracies and varying precision.

Therefore, critical inspection and quality assessment of the data at hand should always precede making any final conclusions and big picture executive decisions. Low quality data should never be assigned any level of authority. Always have your data collection and processing methods checked by a data scientist before putting your data-based insights on a pedestal.

2. The Lazy Neglection

Even if they all have entries for the same columns, not all rows in the data set are comparable. In their determined pursuit of data-driven insights, many companies are making one heck of a mixed drink out of not-that-great-matching ingredients. It is crucial to understand and accept that data items are often acquired from different sources, under incomparable conditions, at very different times, and for various purposes.

Our app development agency in London takes great care to ensure quality and correct data processing in our clients’ digital products.

Even if they all look the same at first glance, not all data entries can be integrated and analysed together without introducing some serious biases. Again, this needs to be taken into consideration when designing the data collection and processing strategy, as well as when drawing conclusion from the results of the analyses.

3. Acting Before Thinking

The field of Big Data research and its applications is pretty fascinating. So fascinating that it makes a great number of companies jump into data collection and analysis without carefully outlining a follow-up plan and objectives. What will the insights be used for? In which contexts will they be applied? What are the most relevant data sources? If you haven’t figured out the answers to these questions yet, sit down with a data specialist and think everything through.

As obvious as this last point might seem, delving straight into data collection and analysis with the ‘Let’s see what’s gonna come out of this’ attitude is quite common practice. This is why our app development agency in London always advises clients on their Big Data objectives and strategy. Do you feel that you could use a helping hand when it comes to data-driven insights generated by your digital products? Send us a message and let’s have a chat!

Marek Hasa
Written by
Marek Hasa
Related posts
Computationalism & how we manage our lives (Pixelfield Podcast ep. 4)
Business | Podcast - 10th December 2019
By Pixelfield team
Google cities & the end of privacy – Pixelfield Podcast, ep. 2
Business | News | Podcast - 8th December 2019
By Pixelfield team