Technology has since time immemorial served humans and will continue to do so with its innovations, technological advances and inputs. Each era brings forth new technologies, methodologies and other variations that help satisfy human needs and make their lives easier. Be it the Industrial Revolution of the late 1800s or the current wave towards robotics, machines and humans have long formed a timeless association. Presently, there’s an inclination towards incorporating “data” in mainstream technical types of machinery and engineering. The expulsion of data has given rise to several streams such as data science, data analytics, machine learning and other fields.

“You want everyone to be able to look at the data and make sense out of it. It should be a value everyone has at your company, especially people interfacing directly with customers. There shouldn’t be any silos where engineers translate the data before handing it over to sales or customer service. That wastes precious time.”

The words mentioned above by Ben Porterfield focuses on the need for making data analytics flexible and customer-oriented for better utilisation. Sometimes a complex and intricate technology such as data analytics can cause confusion amongst the end-users if not educated and prototyped accurately. Therefore, enrolling for online analytics courses offers a means for a successful understanding of this domain and helps budding professionals navigate their careers with finesse. One such program is the XLRI financial analytics online course that provides deeper insights into the analytics sector.

Getting to Know the Different Types of Data Analytics

Data analytics is a vast field with its applications in decision-making, automation of complex tasks, gathering insights about minute data-sets, analysing and identifying patterns and clustering information based on certain common traits. A plethora of online analytics courses are instrumental in teaching various data analytics types for better outputs and results.

Here are the different style of data analytics that businesses go for in today’s digital realm:-

• Descriptive Analytics

Descriptive analytics, as the name suggests, compares the company’s data with previous historical data. It combines and juggles raw data from several sources to render meaningful insights. These signals are mere indicators of whether the commands, information or output displayed is correct or not; however, it’s vital during decision-making stages as it points the board members in the right direction.

Descriptive analytics performs real-time analysis of data in bettering future decisions and strategies. Social media analytics are potent users of descriptive analytics.

• Diagnostic Analysis

The diagnostic analysis is the branch of data analytics that deals with a particular problem. The scope of analytics lies within solving and offering results for that problem or issue. Therefore, data engineers focus on gathering insights, pattern searches that can help them find answers.

Diagnostic analytics is time-consuming since it “diagnoses” each problem and collects data and then stores it in its memory for further analysis and deductions.

Retail companies and industries that require data scraping utilise diagnostic analytics. Prime examples of diagnostic analytics include Amazon, Myntra etc.

• Predictive Analytics

Predictive analytics gives information about events that are likely to happen in the near future. Prediction based analytics provides real-time deductions of outcomes that have a high probability of happening.

Predictive analytics is critical in financial risk management, wherein it is used for predicting the outcome of potential financial risks, hazards and other company’s losses. The XLRI financial analytics online course can help learners learn about analytics protocols for minimising risks.

The data analytics types mentioned above all play a determining role in mapping out business decisions, policies, financial losses and diagnosing problems. Hence, the variety of online analytics courses can enable professionals to get more profound knowledge about this domain.

Impact of Analytics on the Day-to-Day Lives of the Consumers

There are exciting data analytics projects ideas for young professionals. Moreover, there has been a noticeable impact of data analytics on the daily lives of consumers. Several data analytics have found homes in human lifestyles and continue to boss the data-backed technologies.

The data backed mechanisms have paved the way for the invention of practical and user-friendly applications utilised efficiently.

Here’s how data analytics has entered human lifestyles:-

• E-Commerce Websites and Online Shopping

Those days are long gone wherein one had to travel to markets for purchasing clothing, entertainment and other items. With several E-commerce websites and the luxury of online shopping, users can buy almost anything online.

These e-commerce giants apply data analytics practices to study their customer’s purchase patterns, locations, preferences, and other information. This helps in suggesting products that are preferred by the consumers.

• Combating Crime

Data analytics helps police combat crimes in a specified location. Utilising “predictive policing” techniques of data analytics, police officers can find the next crime’s whereabouts. Crime stoppers in association with IT professionals can map out the exact location of the next potential crime, and it can be stopped.

This leads to safety among the public and creates mutual trust between police and commoners.

• Breakthroughs in Health-Care Industry

Data analytics has changed the healthcare industry by creating an electronic database of patients history and allows the doctors to continue the diagnosis more effectively. Furthermore, wearable technology that records users’ sleep, heart rate, and BMI has become quite popular and has made healthcare more practical and reliable.

Healthcare practitioners’ Insights comes in handy while treating patients, putting them on special diets and supplying medicines.

• Music Streaming Channels

With the advent of data analytics and active data collection, music streaming has gotten more personalised over the years. The traditional radios have been replaced with music applications that allow the luxury to listen to songs based on mood, preferred genres and other metrics.

Potent examples of music streaming channels include Gaana and Spotify.

The world is reaping the benefits of data analytics through user-friendly applications, software and technologies. Professionals looking to get a deeper understanding of other data analytics uses can join several online analytics courses.

Conclusion

As can be seen from the points above, there are heaps of applications utilising data analytics models to make user lives easier and fun-filled. Professionals can enrol for programs like the XLRI financial analytics online course to formulate a career in machine learning or big data analytics.