Big data is the most trending topic in the technology world, but it is a complicated thing also to consider. We have seen the rise and fall of many big data startups, and in light of this, we are trying to put forth some guidelines for big data startups to succeed. These guidelines are given by keeping the new-generation entrepreneurs in mind who want to get into emerging technology fields to succeed.

This is a long story; however, jotted down here in short. As a startup entrepreneur, you need to choose your business battles very wisely and try to build a community around what you offer. However, if it is big data, then it doesn’t require an additional cheerleader. Without further, ado let’s get into the point.

Guidelines to big data startup business aspirants

1. The infrastructure need is challenging

Building infrastructural tools for big data is difficult on the one hand, and selling them too is difficult on the other hand. This gets your troubles doubled, while you think of the big data tools like Hadoop, MapReduce, NoSQL DB, and real-time data streaming/processing systems, etc. The users need to have a lot of education and insights. This makes it mandatory for the providers to offer significant support to the users by addressing all their concerns timely and satisfactorily.

When it comes to big data applications, whether they are focused on specific workloads of various industries or applications to handle broader tasks like data visualization etc. are made easier. However, these sophisticated applications are harder to build, but the prospective customers can oversee how it can be made useful or this compared to what already exists. You will be able to sell big data applications directly into the lines of business without the need to invoke the central IT systems at all, which means that there is only less friction ultimately. Once if you start to talk about removing, replacing, or adding systems or putting sensitive data, things can be more complicated.

2. Friendliness of cloud computing

People have known that the cloud is a very efficient solution for businesses. Nowadays, even if you sell infrastructure or software applications, the cloud can be an efficient option to leverage. This doesn’t mean simply hosting on the cloud, but it can also be beneficial in delivery services to clients in a cloud environment. You can gain better control over your product or service and a deeper understanding of its potential as it can run optimally on a set of resources.

There is no entering into the customer accounts or setting up on the servers and OS they are running. However, there could be some customized work to connect services with the data sources of the customers, but all get more or less the same thing. In this, most of the provider energy may be spared for product development.

After all, cloud computing will make it easier for users to play around with their products. For startups, this makes things much easier to get started, play around with the product, and prove the value of their tools. However, this is not so in all the cases, especially when you are considering larger-scale enterprise software applications which have to handle a huge volume of data. Big data startups may feel such pressure from the larger businesses in the same platform to offer cloud services too as traditional software applications.

3. Developers as your friends

Cater to them if you are a big data solutions providers. On the other hand, if you are providing big data analytics services too as a part of your big data database services like RemoteDBA.com, then analysts are your best friends. Whatever your solutions are, ranging from database to development or analytics solutions, aiming your development efforts to marketing on your target audience is the key to success.

In this case, CIOs may not be the ideal target audience. On target the CIOs, the major problem is that you won’t catch them speaking the buzzwords or answering the specific questions about the overblown concerns as compared to contact the actual users. Instead of this, targeting the actual developers or analysts may be the ideal tactic to work well for cloud startups.

4. Deploy data scientists at the front and the center

This is as much as a strategic marketing approach as well as sales too. This is important as data scientists are the professional who will show the users what is possible for them with the use of data and your big data platform. Expert data analysts are those whom people will be listening to at conferences and presentations.

You can see that almost everyone in the technology sector is already sold on Hadoop as well as NoSQL DBMS technologies already. So, for the marketers, there is little need to explain the merits of these further, and there is also no need to reinforce in terms of variety, volume, and velocity, etc. Discussing integrations and configurations seems to be important, but it is more interesting in a smaller audience who closely follow it unless you are talking about things at a massive scale.

While presenting your big data startup solutions, don’t simply talk about data and the kind of infrastructure you can offer for storing data or processing it, but you need to show them what kind of products you can build with the help of it. You need to point out how such products will help their business to grow further and make use of the real data to fuel their operations. Show then what type of analysis they can run or at the minimum, put it across in such way that you are considering data in a broader context than conventional.

5. Open source really matters if you consider it

Many of the big data startups now tend to rely on open-source applications. Some of the technology they have borrowed like Hadoop and Storm etc. Some others which they create by their own also come into the picture. In many other cases, it could be a fine combination of both with added functionality as to things like HBase. These type of projects are so popular because of community support.

The goal of technology in the open source arena is to create a solid community of experts working on the same set of codes to improve and streamline it. In such a scenario, you need to really get out and try to promote the technology inquest and explain every turn of it as to why it is so important to get more people willing to hack on the technology.

However, you may not be able to always count on any random startup that opens sourced the code, but only those companies which are pushing their projects to win a bigger community around their technology only stand out.