Technology

Employing Big Data for Startups

This column is authored by Blake Davis, Digital Marketing Manager, Life Education Australia

big data startupsIt goes without saying that in the 21st century information is the key to success in the business world. Still, in order to extract this information and make it as valid as possible, you need data; volumes and volumes of data. For example, a transportation giant Uber is currently utilizing big data in order to make more efficient routes for their drivers. This way, they hope to predict where their passengers want to go before they even enter the car. There are many other examples of this at the highest tiers of the business world (NFL, BMW, etc.); still, is such a thing possible for an aspiring startup as well? Let’s find out.

Data-Driven Decision Making

One of the most common misconceptions in the business world is that an experienced businessperson somehow always knows what to do. Moreover, a lot of people prefer to attribute this phenomenon to the notion of gut-feeling. Now, while there are those who believe this is a mystical power only the chosen ones have at their disposal, in reality, things are much simpler than that.
You see, over the years, an experienced businessman subconsciously acquires huge amounts of data. Based on this, they have the ability to recognize patterns from their previous successful or unsuccessful ventures and make decisions based on that knowledge.

The best thing about decision-making that is based on big data is that it allows you to skip years (even decades) of failure and make your choices similar to those aforementioned. The problem with learning from your own mistakes is the fact that 9 out of 10 startups end in failure, which can be incredibly expensive. With big data, you get to skip this part altogether and get a start similar to those of your much more experienced counterparts.

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Quantity or Quality

According to some, quantity is a quality of its own kind, but when it comes to big data, this claim is not necessarily true. According to experts behind Picnet IT services Sydney, it is the quality and not the quantity that yields the best results. In other words, it is not how often you ask the question, but the content of the question that counts. This is where predictive analysis comes in big time. Through an elaborate system of data engineering, deep learning, and pinpoint-accurate data visualization, it can give your company a much more cost-effective start.

The Importance of Early Start

early startImage source: Wikimedia Commons

Another thing you need to keep in mind when it comes to big data is the fact that an early start gives you a huge advantage over your competitors. The earlier you start harvesting data, the more you will be able to process. Furthermore, even if a piece of data you stumble upon isn’t relevant for your work at the moment, it might become in the future. Sure, some would argue that this could easily lead to great volumes of unnecessary data, but if you know how to ask the right questions (something we already discussed in previous paragraphs), this shouldn’t be an issue.

This is also why you might want to think about scaling your big data implementation over time. You can easily buy add-ons to the systems you already have and, more often than not, this tends to be the most cautious (and therefore – the safest) approach to the matter. Keep in mind that even the greatest companies today started with a few gigabytes of data.

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Different Approach to the Market

Finally, a proper use of big data can allow startups to get a better sense of the market they are engaging in. This can allow them to customize their customer engagement methods, save time and even have more success in the fight for their share of the market. Probably the greatest problem of being a startup lies in the fact that you are often outgunned by your counterparts. They have greater budgets, numerous workforce and an already established network of contacts. This means that the only way for a startup to outperform them is to adopt those policies that bring better ROI and thus bridge this gap.

In Conclusion

There is a common saying in the online world that says big data is like teenage sex: “Everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it”. The numbers, however, speak otherwise. According to one survey, less than half of large companies are implementing big data solutions. When it comes to startups and small companies, the numbers are even lower. Luckily, while to some this represents a pessimistic piece of information, for an aspiring business owner, this can be a one-way ticket to the top.


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