Why your business needs data science

Whether you know it or not, your business collects a lot of data. Data science helps you use that data as a powerful tool to improve your business.
Jan 27, 2020 • 5 minute read
Zohaab Ishrat @zohaab85
Technical Co-pilot
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Data science can help you make better decisions, better products and better marketing campaigns

Businesses keep looking for new ways to grow and expand by utilizing any means (legal of course) necessary; to overcome competition, to create brand awareness, to make more profit and avoid any possible loss (financial, reputational, etc.). They employ every strategy they can, use every latest technique and method available use all the essential information they can gather to expand their empire. Such is the world of business. If it’s not flourishing, it may very well be shrinking in comparison to the competition.

One very powerful tool that more and more businesses are taking advantage of is data. Data is everywhere, and it's being produced in abundance with every action your business takes. Our choices, our priorities, our likes and dislikes, etc. are all data. Very valuable data, in fact. But that data is of little use to you and your business if you don't know how to interpret it.

What is data science?

Data science encompasses skills like how to record or store data, how to analyze it effectively and how to extract valuable information from it. Whether the data is structured or unstructured, the objective is to extract knowledge and insight from it that will prove to be beneficial.

Though related to computer science, it's a separate field on its own. Computer science revolves around computers, using programming software to develop solutions and creating algorithms for the recording and processing of information. Data science may or may not involve the use of computers. It has more to do with mathematics and statistics and revolves around the collection, organization, analysis and presentation of data.

Due to the sheer abundance of data produced on a daily basis and maintained by companies and organizations, data science has been made an integral part of IT. As the amount of data grows beyond the analytical capabilities of humans, we have to rely on computers and smart algorithms to do our job more efficiently for us. The process is used to develop ways to efficiently store and manage data, analyze it and gain valuable insight about user behavior and market trends, and even predict future trends and behaviors.

Data Science is a blend of various machine learning principles, algorithms, and tools with the objective of extracting data and patterns to predict and determine the trends of market and consumer behaviour. So, a data scientist does an exploratory analysis of data, discovers hidden insight from it, deploy the use of various tools and machine learning algorithms to observe and analyze data from multiple angles.

Basically, a data scientist will apply one of the following analytical techniques for achieving desired results:

Predictive causal analytics

This involves developing a model that can predict the possibility of a particular event in the future. An example can be of a loan firm using predictive causal analytics to study the payment history of a client and determine whether or not they're likely to make future loan payments on time.

Prescriptive analytics

This is a model designed to make decisions for itself with the ability to modify itself with dynamic parameters. Prescriptive analysis is all about providing advice, suggestions and providing a broad range of options to choose from to associate possible outcomes. Intelligent chatbots and self-driving cars are examples of this model in action.

Predictive analysis (machine learning)

Machine learning is used to process a large amount of complex data. Also called supervised learning, this form of predictive analytics has data already present which can be used to train the machines.

Pattern discovery (machine learning)

Predictive analysis with machine learning already has information which can be used to train the machine. However, if there is no data available, then hidden parameters need to be discovered for the machine to be able to make meaningful decisions.

So, a good data scientist is something more than a programmer, mathematician or a statistician. The role involves knowledge in all these disciplines.

Benefits of data science for your business

After developing a basic understanding, let’s look into why a business may need data science.

Empowering management to set strategy

Data analytics provides information that can help in strategic planning. It enhances the analytical abilities and overall decision-making skills of the management and staff by providing them with measurable insights.

Keeps you ahead of the competition

We've already mentioned this one before, and this is what data science does best. It can process a large amount of data to determine trends and predict future behavior. This provides valuable insight into consumer behavior and emerging marketing trends. This can be used to gain a competitive edge in the market.

Increasing staff alignment

By making the employees more aware of the trends influencing your business and its revenue, you can align your employees behind common goals. Giving employees a transparent view of the data that's shaping your performance means they understand and can buy into your strategy, and help course correct when needed.

Identifying measurable targets

Data science provides valuable insight into the areas that can be improved upon. By constantly measuring trends in your business, you can see at a glance the areas where you're performing well and the areas you need to improve. This can drive innovation and creativity.

Data-driven action

This might be one of the biggest benefits of data science. Your decision making will be guided by actual data rather than guesswork. Before your company takes any action, you'll be able to look at past trends and forecast the likely outcomes of your decision.

Identifies your target audience

Customer data is perhaps the most valuable form of data an organization can get their hands on. Processing this data reveals valuable insight. You may have a preconceived notion of the types of customers engaging with your business. Data science will show you who actually engages with your business. Knowing more about your customers can help you develop products and services, and guide your marketing decisions.

Easier talent hunting

Human resources departments can also benefit from analyzing data. Since they're always on the lookout for talent that best fits both the role and the business, their task has been simplified by data science. By obtaining comprehensive data on individuals from social media, corporate profiles, and job search database, HR departments can process candidates much more quickly and pick the right resumés.

These are just a few ways data science can help businesses grow and flourish. Of course, it’s not limited to a particular industry or business, nor does it have anything to do with the size of the organization. Fortunately, if you're a small business, you don't have to hire a full-time data scientist. You can find a freelance data scientist to help pull together the data your business collects and present it in an easy-to-understand form.

All businesses have data, and if they're not analyzing this data and using it to set strategy and identify trends, they're squandering one of their most valuable resources.

Bodite na tekočem

Naročite se na naše glasilo, da boste na tekočem pri pomembnih zadevah.
Hvala za naročilo! Spremljajte svojo prejeto pošto za naslednjo novico.

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