Data Analytics

Why is Data Analytics Important?

What gets measured, gets managed." -Peter Drucker

This quote by the late management guru, Peter Drucker, represents why most companies invest in data analytics. How can you manage or optimize your business initiatives if you are not measuring their outcomes? Just because you measure something does not guarantee that you will manage it, however, measurement is the starting point.

What is Data Analytics?

Data analytics is the science of analyzing raw data to draw key insights, draw valuable conclusions and take action to increase business efficiency. Techniques of data or business analytics can reveal trends and metrics that would otherwise be lost in the mass of information. This information is used to optimize processes and increase efficiency of a business or system. That sums up why data analytics is important.

Data Analytics Types

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Data analytics is broken down into four basic types.

  • Descriptive analytics describes what has happened over a given period. Have the number of views gone up? Are sales stronger this month than the last?
  • Diagnostic analytics focuses more on why something happened. This involves more diverse data inputs and a bit of hypothesizing. Did the weather affect beer sales? Did that latest marketing campaign impact sales?
4 Types Of Data Analytics

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  • Predictive analytics moves to what is likely going to happen. What happened to sales the last time we had a hot summer? How many weather models predict a hot summer this year?
  • Prescriptive analytics suggests a course of action. If the likelihood of a hot summer is measured as an average of these five weather models is above 58%, we should add an evening shift to the brewery and rent an additional tank to increase output.

Business Context

So data analytics is important because it helps businesses optimize their performance. Adopting analytics into a business means better business decisions and better understanding of market trends. This means better products or services made available more efficiently & cost effectively.

Importance Of Data Analytics

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Analytics is a powerful tool in today’s marketplace. Industries and organizations are generating vast amounts of information which has heightened the need to interpret and analyze that information to gain competitive advantage in the market. According to a recent study by MicroStrategy, companies worldwide are using data to:

  • Boost process and cost efficiency (60%)
  • Drive strategy and change (57%)
  • Monitor and improve financial performance (52%)

Research also shows that, over the next three years and beyond, 71% of global enterprises predict their investments in analytics will accelerate.

These statistics further ascertain why analytics is important for organizations of all sizes. Another way to look at it is to evaluate what it would be like to NOT have information on your business. The following quote by Arthur C. Nielsen, the founder of ACNielsen, highlights that any investment made in Business Intelligence & Data Analytics will be less than the price you’ll pay if you don’t know how your business is performing. Consider the missed revenue opportunities and potential cost savings you would be giving up.

The price of light is less than the cost of darkness." -Arthur C. Nielsen



Data Analytics And Society

It is high time we started thinking of Data Analytics and Society as two inseparable components of our ecosystem. In the 21st century technology and data analytics with tools like artificial Intelligence, machine learning & deep learning have great potential to impact society positively. Today we have the largest amount of data ever available to us. We also have tremendous capacity to capture, analyze and utilize data and create products & services that solve society issues.

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Collecting strong data sets on a social, health or environmental issue allows academics and researchers to understand the severity and impact of any issue. Then Academics, businesses, NGO’s, and governments can mobilize their leadership & innovative skills to tackle problems identified using data.

Data Science & Analytics has many many buzzwords like “AI”, “Deep learning” and “Big data”. It is a growing field with a lot of potential but it is also important to ask questions like why need for machine learning? What do we use big data for and why? How can we benefit from the technology and help the rest of the world and society?

Volunteer Work

Data Analytics contributes greatly to society through volunteer work with a socially oriented data science program/ organization. Some socially oriented data science fellowships, typically in conjunction with nonprofits and local governments, are available. These platforms offer a closer insight into the myriad of problems that may be addressed through the application of data and analytic tools. There are few data-science organizations that are solely focused on social good and offer numerous opportunities for volunteering. This can be through mentoring or using your data science skills to help solve a social problem in one of their projects.

We can use our analytics skills and contribute through competition platforms. Platforms such as Kaggle hosts competitions intended to solve problems with social & real world impact. Resourceful data scientists and analysts can identify & solve social problems on their own, with the data available to them. For instance, a great resource for data is the GapMinder Foundation which provides statistics to understand global trends and issues.

Governments & Global Organizations

Data Analytics in the form of Big Data is also being used to help improve the world we live in. Urban planning with systems like utilities, energy, housing, transportation, and infrastructure is one such key. Many cities are using big data to convert their municipalities into smart cities and in solving issues related to parking, pollution, and energy consumption.

Big data is playing a key role in protecting the environment. Big data offers alternative solutions to deforestation so that we can lower our carbon footprint. Similarly, it also offers the opportunity to protect endangered species and mitigate poaching.

In Public Health, big data allows scientists with increased ability to predict patterns in diseases and mutations. They are now coming up with algorithms that can help predict infections based on data — hours before physical symptoms appear.

For organizations like UNICEF, big data is key to their success. They can deliver immunization, healthcare, and water to some of the world’s poorest populations by analyzing big data.

There are so many opportunities to use data analytics for society and make a meaningful impact. Data science & analytics work is getting visibility in organizations that are oriented towards serving the public good. Governments, SMEs, NGOs, and other Social bodies are beginning to recognize the importance of analytics, particularly its data driven insights, predictive capability, and evidence-based recommendations. In the 21st century data analytics and society can and should come together to realize unprecedented potential in tackling pressing issues in less privileged environments.