Adopting Analytics: The Challenges for Start-ups

In business, agility is the big difference allowing start-ups to achieve the skill to compete with larger enterprises and industry powerhouses. This becomes incredibly important when implementing new technologies.

Whilst larger organizations have to answer to hierarchies that can make the process more difficult to implement changes, start-ups can readily adopt the latest technologies such as big data analytics and intelligent machine-learning tools.


The unfortunate fact is that agility is the sole advantage that start-ups hold over large enterprise companies when it comes to adopting new tech. Notable challenges they face include more limits in their budgets, talent hire costs and a lack of resources for building, deploying and maintenance of a high-quality data system.

Despite these challenges, adopting a big data infrastructure is a worthwhile endeavour providing immense benefits. Organisations using big data and analytics are 36% more likely to beat their competitors in both revenue gross and operation. An efficient analytics infrastructure provides a base for businesses to make informed decisions on all aspects of their business – including the designing of products and supply chain efficiency.

Business leaders stand to gain better confidence in steering their businesses successfully through big data.

Adopting Analytics

Many early adopters throw venture capital into the latest analytical tools to arrive on the market, but it is not always the solution for a start-up with a precarious financial standing where profitability may not have been attained yet.

The ideal approach is starting small and slowly scaling up on technical investments one by one. A secure and resilient data lake is a solid starting point, allowing you to store all structured and unstructured data at any scale – able to store your data as it is, without running it through any analytics tools.

It will require the gathering of a large amount of data that cannot be analysed or derived value from, but it does get things started in gathering data that will drive more costly analytics tools that you incorporate later. Once these tools are added, data scientists and developers can access your data lake without needing to move it to separate systems.

With global big data market projections highlighting a $103bn 2027 growth, it is unavoidable for any business of any size to get serious about adopting high-value data analytics systems. Whilst costly as an investment, start-ups can still be an important part of data transformation that affects almost every industry sector today.

For more information on big data analytics and any upcoming big data events, check out the upcoming events from Whitehall Media.