A Practical Approach To Big Data

A Practical Approach To Big Data

Big Data is the most talked about term in any organization since the last decade. Whether it’s the people from IT department or business/operations department, everybody is trying to get their head around the company’s Big Data and gather insights from it. Today, almost all the organizations have a colossal amount of data on their consumers. This data, if thoroughly understood and studied, can prove to be of immense value. Most of the organizations (at least the successful ones) are realizing this fact, and trying their best to devise a practical roadmap/strategy to make the best out of the heaps of data they have.

A failed Big Data strategy is worse than not having any data at all because having an impractical approach will not only waste your time but also lead you in a completely different direction. The age-old saying “one size fits all” doesn’t work in the context of successfully implementing insightful Big Data systems. For that, you need to gauge your requirements and the end goal you want from your data. And, not to forget, you also need to be aware of the level of technical competency of your team.

If you’re working with the technical team and have the responsibility of making sense of the organization’s data, it’s imperative to have a clear understanding of how things function. If you find yourself lacking in terms of technicalities, there are many online Big Data Certifications that can help you get better armed to tame the beast.

To stay ahead of the curve in this ever-competitive world, and not let the competitors overtake, it’s incredibly crucial for any organization to make the most of any data they have. Often, organizations have tonnes of data, but neither the stakeholders nor the tech people have any idea of what to do with that data. The tech team might lack the required skills, whereas the managers and other stakeholders might not grasp the potential value of the daily or hourly factory and customer-service data they possess. More often than not, this lack of understanding is what keeps them formulating an effective strategy, which, eventually prevents them from excelling in their domain.

Being clear about the business problems and having an understanding of their challenges and opportunities will help the stakeholders better access the organization data. This forms the unspoken first rule of any Big Data implementation strategy – understand your requirements!

If you’re indeed looking for a long-term relationship with your Big Data, and are sure it’s not just a fling, it’s recommended to get an experienced technical team in-house, with experts on the subject matter in-house. Understanding your requirements and communicating them with the Big data experts will help them get a better idea of your end-goals. This, consequently, will help them build better and long lasting systems.

Let us look a five-step roadmap that’ll take you to your destination:

  • Find a balance between tech-led and business-led planning: One ongoing debate while implementing any Big Data architecture is that whether it should be business-led or tech-led? So much so that people have even named these approaches, with business-led being top-down and tech-led being bottom up. In all honesty, your fit is for you to choose. Both of them have their merits, but none can succeed in isolation. You need to balance both correctly for best results. If you find the tech and non-tech people of your communicating in mutually incomprehensible jargons, it’s better to decide on a common language for both; else your efforts will be as good as none.
  • Understand that there’s no “perfect Big Data technology”: Deriving insights from your Big Data requires you to focus on various aspects. This calls for using multiple tools and frameworks. So, drop the idea of working with the “best Big Data technology”, because there is no such thing. Like everything else, this too boils down to your needs and requirements. Having said this, Hadoop does play a vital role in any Big Data project. But, there’s much more than Hadoop in the world of Big Data if you’ve to utilize your data to the fullest. Different use-cases and environments require different technologies, and it’s best to talk to experts and thoroughly research to find your fit. Don’t go for any technology because it’s the new thing in the market without understanding how it’ll help your cause.
  • Understand your use-case: Big Data analytics caters to a variety of use-cases like improving the accuracy of your marketing campaigns, finding fraudulent entries, providing better customer service, reducing downtime, and many more. All of these have different starting and end points. Just like there is no perfect technology, there isn’t a standard starting point either. Be aware of your use-case, and then take your first steps towards solving the problems with Big Data. The strategies you make should reflect what your organization wants to achieve, and also should take into consideration the existing technological investments. Knowing these things will help you pick the best technology and proceed in the right direction. Make sure to always start with a question!
  • Make long-term strategies and plans: We’re sure you don’t want another set of Data Silos that’s difficult to manage and too expensive to integrate. Always be two steps ahead while laying out any strategy. Have a comprehensive SWOT analysis to understand the challenges and threats you’re likely to face in the future, and device the plan accordingly. There will be times when you’ll need to make technical choices, but you should be clear as to how they’re going to impact in the long run, and what can be done to deal with it.
  • Go flexible and Agile: This should be done sooner than later while implementing any strategy. Being agile will enable you to go back and forth in case of errors smoothly; this will also ensure overall better management of your Big Data system. Successfully implementing Big Data solutions is no mean feat, and there are always sources of errors. Using agile or other iterative techniques instead of a “big bang application development” approach will ensure that you do not miss out on any demands.

Following the steps mentioned above will ensure that you’re on the right track. The journey through Big Data is a long one, and taking the right path is the first step towards reaching your destination!