Analyzing large and varied sets of data to uncover hidden patterns, correlations, market trends, preferences, etc. better known as data analytics is by no means a new field. It has taken some for organizations to embrace it. But today, with the advent of technology and the availability of more data, it is starting to be widely used by businesses for their growth and development. More professionals are taking data analytics courses to equip themselves with skills and tools that will their organizations and themselves.

 

10 trends that will shape the future of data analytics have been put together below:

 

Internet of Things (IoT): The IoT market is growing at a fast pace and expected to expand 4 times its size by 2022 owing to the further advancements in the fields of data processing and advanced analytics.

 

Hyper-personalization: The businesses do not need to deliver one product through a hand-picked set of marketing strategies anymore. Using data analysis, they get in-depth and accurate knowledge about customer personas, behavior, preferences, etc. and understand customer needs much better, thereby, being able to tailor products and/or marketing strategies to suit the customer. More brands are embracing this for their success.

 

Artificial Intelligence (AI) and Machine Learning (ML): AI and ML are being adopted by businesses extensively to analyze big data about various aspects of their functioning and strategize accordingly for better outcomes. This is especially true in the case of improving and providing a seamless customer experience.

 

Augmented Analytics is being adopted by organizations to use the power of machine learning to automate data preparation and presentation, and to produce rapid outcomes in data-driven domains.

 

Predictive Analytics is being widely embraced by organizations to solve problems in an insightful and structured manner. Organizations are using this tool for forecasting future behaviors for greater profitability, minimize risks, improve business operations, etc.

 

Cloud services offered by various providers and platforms have eased business concerns about handling and storing today’s big data. This technology is here to stay.

 

Edge Computing has solved connectivity and latency challenges associated with data travel and has revolutionized technology in this age of IoT-enabled smart devices. Edge computing will consolidate its position with greater usage of drones, wearable technology and autonomous vehicles.

 

Behavioral Analytics is currently being used extensively by organizations for personalization, customer intelligence and marketing. However, efforts are on to explore more ways of using behavior analytics especially in smart city projects, traffic pattern identification, track medical shipments and cold storages for breaches, etc.

 

Graph Analytics: This technology is used to map relationships in big data as well as finding the strength and direction of such relationships. There is a strong case to apply it to areas such as detection of financial crimes, conducting research in bioinformatics, logistics optimization, etc.

 

Blockchain Technology: With the success of cryptocurrencies which use blockchain technology, data scientists and business organizations (especially financial institutions) are considering merging big data with blockchain technology to expedite processes and create better fraud detection mechanisms.

Want to know how can this course help in your profile?