Analyze your Company’s Data with High-Performance Computing for Revenue Growth

Data is the new oil, a statement to which every company, regardless of industry or country, has agreed. Your data is an asset and can provide deeper and more detailed analysis, which lays the foundation for business development. Data utilization is a challenge for everyone, from a startup to a Fortune 500 company, because many companies don’t know what data they need to analyze or how to understand the analyzed data. The way an organization uses and learns from its data plays an important part in the overall growth of the company. No wonder bigger corporations have dedicated professionals to prepare analytic reports. High-Performance Computing (HPC) is the Holy Grail for this job. This technology offers massive computation power for huge volumes of data at regular intervals. For instance, a company planning to analyze Twitter data can use traditional computing to generate personalized insights every hour as opposed to every minute using HPC.

What data are we talking about

There is a lot of data in our systems and the outside Web world. However, we don’t need to analyze all of it. Following are some of the important and proven types of data that result in awesome analytics using HPC.

Sales and Marketing Data

The information specifies how the sales happened over time and salesperson-related data. There might have been many cold calls and some hot leads done in the past week, but we might end up with a few accounts. The deal closure ratio for every month and the annual performance of a salesperson will give insights into what can be improved upon to close more deals. The marketing campaigns we run on social media and how many have resulted in sales of our products.

Support data

The often-neglected gem of data is related to the support cases handled by customer service executives. The support is mostly focused on resolving the issues and improving the quality of products and services provided by your company. The interactions with customers through calls and chats are valuable for the company. Analyzing this data often gives insights into the gaps that need to be closed and focuses on improving the standard of the products delivered and services offered by catching a potential issue before it occurs.

Social Media Data

The most powerful data on the web is often easily visible and is also the most scattered. In technical terms, we call it unstructured data. What is the Internet talking about? What is trending? What are people shopping for? What are people complaining about? All these questions will be answered if we dig into Social Media Networks and find their patterns. Many companies keep an eye on what their competitors are doing by crawling their websites and news feeds. Some companies dealing with financial institutions fetch data from thousands of news articles every day. The best option to analyze this type of data frequently is to use high-performance computing !!!

What volume are we looking at?

Gone are the days when our data is in megabyte Excel files that we needed to analyze. Nowadays, the smallest file size of the data we see is in gigabytes (GB). Typically, the files that companies deal with every day are measured in terabytes (TB). Some fortune giants have data in PetaBytes (PB).

High-Performance Computing Applications and Analysis tools handle this data with Grace.

But it’s Costly!

HPC is always a costly affair as it involves a computer cluster with big, fat network servers and enormous storage. However, the cost is worth the results you get out of analytics as you are improving your company’s assets by generating meaningful insights out of the data that will be useful for your company’s growth. The silver lining is that many HPC service providers take care of your analytics requirements at competitive prices.

How should you analyze

  • The first and most important step is to determine what you want from the analytics. We had seen the types of data and possible analytics surrounding each of those. A company cannot have all the possible analytics to be useful, so the decision to choose the necessary and useful analytics will help in the company’s revenue growth.
  • There are a few HPC analytical tools available in the market, and companies like IBM and AWS can help you build your personalized solution. Based on your data and requirements, you might need to do a little research and see some demos of the analytic tools before finalizing the best one.
  • However, selecting a tool is insufficient for our mission; you must have a dedicated team of professional analysts to extract meaningful insights from the analytics. The analytics tool will generate reports that have more summarised data, and you wouldn’t be spending time and effort understanding what you want as there are analysts who are experts in providing you with the best insights useful for your company’s growth.

Common Mistakes to Avoid

  1. Try using the existing tools instead of building something on your own, it’s always better not to reinvent the wheel and use the trending and leading market tools, though it involves substantial costs.
  2. Have a watch on the competitor’s data, but do not compare every minute detail with your company’s. Healthy competition is better, but many times we compare apples to oranges.
  3. Archive your data instead of deleting it. As historical data always plays an important role in analyzing trends and predicting the outcome accurately.

 

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