Top trends to watch out for in Data Analytics

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Future Trends in Data Analytics

Data analytics is not the next big thing in the business world; it is ‘the’ big thing in the business world. Data analytics has transformed the way we do business by providing actionable business intelligence, which was previously unavailable. Big data analytics companies are changing the way they analyze data by implementing the latest technology in data analytics.

Being such an important topic, you must keep up with the latest developments in the field of data analytics.

This article will try to take a peep into the future and see what exciting stuff does the future hold in the field of data analytics.

Significant trends in Big Data Analytics

The emergence of specialized jobs

Until now, having a data scientist or a data analyst in your team would have sufficed. But as the realm of data analytics gets matured, more specialized, industry-specific roles will be generated in the future. With more experienced professionals looking up to the field of data analytics as a lucrative career option, the specialization will be the key to survival.

For example, Any company would prefer to hire a chemical engineer who has worked in the chemical industry instead of a data analyst with no real-world experience in the industry.

Automation

The symbiosis of AI with data analytics will prove to be a boon for businesses in the future. Sophisticated AI systems will make sure that a lot of processes in the field of data analytics are automated. According to an estimate by Gartner research by 2020, 4 out of 10 tasks in the field of data science shall be automated.

This will leave the mental faculties of human data scientists free to explore new horizons in data analytics.

The field of data analytics will become much leaner and faster with the help of automation.

The emergence of Data as a service

Humans are producing 2.5 quintillion bytes of data every day. Add this to the data that will be generated by 20.4 billion IoT devices that will be in operation by 2020.

Such humongous amounts of data is going to open up possibilities of using data as a service.

DaaS(Data as a service) is a business model in which the companies providing the data provide it over a cloud infrastructure to clients. Organizations around the world are using various DaaS services to understand the nitty-gritty of their business better and to know more about their customers so that they could gain a competitive advantage.

With internet speeds increasing worldwide, DaaS will penetrate more areas, and a larger number of companies will onboard on to this service.

Some companies have already created a successful business model by selling data. An excellent example of this would be a company called D&B Hoovers, which provides data on various companies.

IoT data analytics

IoT devices are going to rule the roost in the digital arena in the coming future. There are going to be billions of IoT devices shortly, which will help in every arena right from logistics and transportation to space exploration. IoT devices contain sensors that, while interacting with the physical environment, will produce a lot of data sets.

These devices will produce quintillions of bytes of data that will require processing using state of the art big data analytics solutions. There is no point in using IoT devices into your business if you do not have the corresponding big data analytics solutions to use the data provided by these IoT devices.

Specialized IoT data analytics solutions will be required in the future to deduce inference from data generated by IoT devices.

Regulations

As we have seen with GDPR, there are going to be more stringent regulations regarding the use of data. This will have an overbearing effect on data analytics as businesses will have to upgrade and improve their method of data collection.

There will be a new set of data privacy experts, which will aid businesses in mitigating the regulatory hurdles.

Data Quality management

As we will face massive amounts of data, the quality of data will have an impact on data analytics. Hence data quality management will gain prominence in the future. In this arena, tools and methods will take shape, which will ensure that the data which is free from errors. Upon data collection, predetermined processes will clean it to ensure that it is of high quality.

Data quality management shall encompass not only the collection and cleaning of data but also its distribution and management across the lifespan of data.

Eliminating bad data and keeping the good one will benefit your organization in many ways; one of them is reducing costs incurred due to poor data quality management. According to research, poor data quality management costs $ 15 million annually to large organizations.

Increased use of NLP

As the field of data analytics gets matured, voice or NLP(natural language processing) querries are bound to rise. Research predicts that by 2020 half the analytical queries will be generated through voice or NLP or automatically generated. New tools will help data analysts in using the various functions of an analytics system using NLP or voice.

Users of the future will be able to utilize virtual assistants to retrieve meaningful information from data sets. Using data analytics won’t remain that complex in the future as anyone would be able to use it through simple voice commands.

Conclusion

We are entering a new age in terms of data analytics. Sophisticated AI, machine learning systems, and stuff like NLP and data quality management will increase the efficacy of data analytics systems shortly. The power of data is going to be multiplied exponentially with the use of the technologies mentioned above.

If your business is not thinking about using this power, then you might be on the verge of losing out a fantastic opportunity. Data analytics will help you to get a leg-up on the competition and understand your customer as well as the market in a better manner. It is advisable to hire the top big data analytics companies, which will help you in leveraging the power of big data.

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