Common slogans in almost every company are Big Data and Data Science. Today’s business world is full of Big Data products, and businesses are continuously investing in these products.
Many companies have initiated steps to modernize their data platforms with the idea of allowing their employees to monetize their valuable data. However, most of these businesses are not enjoying the benefits of this.
Many companies don’t have a single idea regarding how data science produces value. Also, there is a major delusion that Big Data tools are the first investments these companies need to make to see the value of data science.
As IT consultants from Acrodex would point out to you, many companies are realizing that they don’t have data scientists to utilize the existing Big Data tools. The companies have the tools, but they lack the right kind of talent and ideas of using them. This article will discuss why your company needs data science consulting before Big Data tools.
Software consultants have successfully convinced businesses the value of agile methodology and lean approaches. Data infrastructure might have made it through the big upfront investment like what happened in the software industry. Big Data companies might argue that their products enable agility.
But the truth of the matter is they are massive and inflexible systems which are only suitable for scaling up systems whose idea development is nearly completed. Big Data tools solve critical problems. But they can’t solve the problems without the necessary kind of talent and ideas.
It’s unreasonable to develop a scalable data environment before even proving some ideas at a small scale. Buying an expensive database without the need of the database is not only wasteful but may not enable the scalability you need. This is like constructing a railway line before the invention of train.
Data science consultants are experienced in extracting a small amount of valuable information from a larger data set (also known as data reduction). This includes sampling, compression, variable selection or choosing the appropriate algorithm.
Dealing with more data than this impedes the development of initial ideas and delays the development of the product. So, putting small before big helps a company to determine the kind of scalable technology required. This helps in making both smart and timely investment in case that time comes.
There are very few companies with the right kind of data science talent. Many companies admit that they may be lacking the right kind of talent, but they have data analysts who can play the part until they have data science team in place. These companies find it hard to hire a data science team while they have already hired a company to develop Big Data tools. This adds little or no value to the company.
Other companies are not sure whether they have the right kind of talent. They have employed people whose job title are a data scientist or have a complete data analytics team. These people can be doing productive data work, but not capable of developing or using advanced data science algorithms. Also, they might be under a lot of stress for working beyond their areas of expertise.
The solution here is to hire an experienced data science consultant. If you are not sure what your data science team can achieve, hiring a data science consultant is the quickest way to find out. This can happen without a conflict between the data science consultant and the data science teams.
Just like an IT consultant, the consultant can work with the existing teams and assist them to be more effective in delivering data science applications. Data science consultant also can help to develop high-level strategies around utilizing Big Data tools to improve the business model. Also, some consulting companies provide delivery teams and assist in hiring people to support the team once the delivery is complete.