Big Data for Startups: What Are the Options?

Businesses of all sizes should be adequately prepared to invest in the infrastructure and resources to collect and analyze big data or obtain it by other means.

Big data is not simply that avalanching amount of data you aggregate in your operations. In the near future, it will become a necessity to compete effectively. However, there is a slight misconception about startup companies and big data.

It is often assumed that startups are unable to take advantage of big data because they have a smaller pool of data in comparison to larger companies. This is not true, as there are plenty of ways startups can also get involved in big data, too.

Here are a few options for startup companies to take advantage of big data to improve both their operations and customer experience.

Purchase the Data You Lack

Ideally, startups should use their own data where possible as it reflects their own actions and choices, but sometimes the pool of data on hand is just very small to work with. In that case, in order to understand your industry and audience better, it might be a good idea to purchase data from other companies or take advantage of free online datasets.

Yet, while this can give startups a good overview of the industry in general, it is only a short-term solution. Once the data is exhausted for useful insights, startups will need to start looking again for an alternative data source.

Another issue is that this is not their data and it should be treated that way. Digging too deep into other companies’ data will not reflect their business and, in fact, may lead to incorrect and irrelevant insights. What’s more, the data might already be outdated. People can change their habits very quickly, and other factors influencing the market can make the data less valid. While sourcing for data externally can be very effective in the short term, startups need to identify the gaps where they can’t use external data to their benefit.

Manipulating the Data You Have

Even if your pool of data is small, you can still work with it. Applying data science to your data does not require it to be large. The most important thing to have, aside from the data itself, is employees who are able to decipher it and put together the insights.

With big data, size doesn’t always matter. With good data scientists, small amounts of data can reveal a lot more than expected. It’s part of a data scientist’s job to bend and twist data in a variety of ways to extract information that cannot be immediately seen.

It should also be remembered that data scientists need solid leadership from business executives. They might be masters of utilizing data, but they ultimately require guidance on the directions to look in to effectively support decision-making. Once a clear direction is provided, they can then collect and analyze relevant data.

Build Your Infrastructure with Professional Help

Alternatively, if startups have the budget and are looking to scale, they can invest in building the infrastructure needed to facilitate and analyze large amounts of data. Yet, it should be mentioned that this will only pay off if there is enough data collected. This strategy may not immediately give results but it can become a major advantage over time.

There is a number of companies out there to choose from that provide big data consulting services. Such services can help startups build the infrastructure they need to store and analyze big data. For example, companies like Itransition usually offer a full range of related software development services, including data lakes implementation. Data lakes are good for starting out on accumulating different data types (structured, unstructured and semi-structured) all in one place in a cost-effective way so that data scientists can analyze them more easily. With such help from the outside, you can also modernize an aging data storage infrastructure to ensure you keep on using your available data up to the industry standard.

Seeking consultation services is a good option for companies with little or no previous experience of handling big data. However, remember that you will need to hire employees to manage this infrastructure for it to be profitable. On top of that, before considering which big data consulting service they need most, startup companies may want to align it with the type of a data storage infrastructure they intend to use.

So What’s the Best Option?

The key point to remember is that a small amount of data doesn’t mean no data. It can still be used in a variety of ways when placed in the right hands and with the right leadership.

Even if you decide that you don’t want to use your own data (or maybe you just don’t have any yet), there are options. You can either purchase it from other companies or use free datasets that can be found online. Just don’t forget that it’s not your data and it will never fully reflect your business.

Perhaps the best option in the long term is to make a solid investment into the big data infrastructure that will enable storage and analysis. Although startups may not be able to return this investment immediately, it will become a reliable source of insights to help the company grow as more data is collected. If startups have the necessary tech expertise at hand, they can build the infrastructure they need without involving a third party, but if they don’t, specialized consulting is a good place to start.

To finish off, there’s really no reason why startups cannot use all of these options in conjunction by integrating them into one robust strategy.