Building a business is hard. 

Gone are the days when businesses could come up with any product and expect it to succeed. But today’s competitive and consumer-centric market has changed the way companies approached the market forever. 

Today, if your business has to succeed and sustain a competitive edge, having a deep understanding of your market and audience is a must. The problem is market analysis is more complex than you think. 

While the internet has made accessing information more accessible than ever, your data collection is highly prone to render biased insights. This is where big data comes in. 

Big data gives you a comprehensive picture of the market landscape, taking the guesswork out of your business. But then the approach to big data analysis changes fast. 

In this post, we bring you five big predictions on how big data would disrupt market analysis in 2021. 

Market analysis and big data: The future of global business

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The advent of big data in the market analysis landscape completely changes the modern business ecosystem. Together, it not only provides data that is comprehensive but also precise and actionable. In short, it helps to understand your product’s viability and market strength. However, your journey to market analysis does not end with collecting big data. 

No doubt, it reroutes your business in the right direction. But the real value comes when you start drawing actionable insights from your data. This means the success of your bid data and market analysis is highly influenced by the quality of questions you ask. 

To make this process efficient, adopting a systematic, lean, and agile process is critical. Keeping a market analysis template handy can be a massive help in this regard. 

So, now when you know how to approach your data and analysis activity, let’s look at the top 5 predictions that data analytics experts have for you.

1. Exponential growth in data volumes

With the exponential increase in global internet usage, the existing data ecosystem is predicted to witness a significant boost. According to IDC Data Age 2025 report, the global big data volume is predicted to reach a whopping 175 zettabytes by the end of the year 2025, the reason being the advent of IoT (internet of things). 

The fast adoption of smart devices by global consumers is attributed to creating this data inflation. From consumer buying behavior to social networking data, every digital activity is stored on the world wide web. But that is not the only interesting element here. 

Experts predict that enterprises will dominate the big data game by a whopping 60% in the near future. This creates a unique opportunity to transform your business into a growth machine. Your complete approach to market analysis can undergo a makeover. 

Having vertically integrated your data generation and collection processes, you have maximum control over the quality and quantity of data. Your big data can be customized and personalized according to your unique business challenges and audience. 

This will give you leverage to understand better and paint a clearer picture of your market. What follows is a superior product with improved customer acquisition and retention policies and optimized experiences. 

2. Migration to cloud systems

The future of big data does not only change the way your work with data but how you store and manage it. Experts predict that there will be steady migration of data storage from local servers to the cloud, further explaining the reason why. 

With such volumes of dynamic datasets to work with, storing and processing data becomes a challenge. The only viable solutions to these complex problems were open-source coding ecosystems like Hadoop and NoSQL, requiring manual configuration and troubleshooting. Moving data to the cloud gives businesses the much-required flexibility and speed for processing data to draw on actionable insights. 

This means with flexible payment solutions like AWS, Microsoft Azure, and Google Cloud Platform, this trend will continue to grow, albeit with some changes. More and more hybrid systems will come into the business landscape. This will be teamed up with multi-cloud ecosystems where businesses would create their data storage systems in multiple cloud platforms, both private and public. 

This means how you choose to perform your market analysis would be heavily influenced by how your company chooses to store its consumer data. The more systematic their data storage systems are, the higher the processing without undergoing redundancy. 

3. Fast adoption of machine learning

The future of big data is heavily shaped by machine learning, improving the quality of processed data every time.

Machine learning experts convict that the ability of a machine to synthesize data is exponentially better than any human. The advanced unsupervised algorithms, deep personalization, and cognitive modeling ensure that a machine can handle data more intelligently, eradicating human bias from the system. 

What is more powerful?

Combining ML (machine learning) with big data can successfully trace the subtle nuances of human interactions through natural language processing (NLP) for pattern analysis and observations. This gives businesses can access to higher-quality insights without human intervention. But that is not the best part yet. 

Many commercial AI vendors provide cost-effective solutions, bridging the gap between traditional ecosystems where businesses lack the necessary skills to create robust ML solutions for their complex processes. They offer connectors to open-source AI (artificial intelligence) and ML platforms without any complex configuration requirements. But that is not all. They go one step ahead of open-source platform troubleshooting and provide powerful features like ML model management and reuse to simplify the integrated ML and big data processing operations. 

4. Privacy is the top priority

As much as the volume of data increases, the future of big data predicts to change course showcasing higher levels of data privacy. But the reason for the sudden rise in data privacy has always been lying in front of you. Today’s consumers are increasingly becoming hyper-sensitive towards their personal data usage by companies. 

With new cyber attacks every day, security breaches, gaps in data protection, and the arrival of multiple consumer data protection laws keeping up all along with the ever-growing volumes of big data is challenging. What follows is significant losses that businesses undergo in terms of revenue and brand reputation in the long term. 

This is a knee-jerking event for your market analysis activity. 

This transforms the way you collect your consumer data altogether. You need to get creative about your data collection methods. While your consumers are data-conscious people, they still demand personalized brand experiences. 

Leveraging this need to collect your consumer preference data is a smart way to overcome this challenge. But you would still have to take permission and create maximum transparency about how you intend to use their information. This will build confidence and authentication around your brand. 

5. Fast data comes first

The future of big data is predicted to be transformed by the advent of ‘fast data’ or what we also call ‘actionable data.’ According to an IDC report, almost 30% of the global data would be real-time by the end of the year 2025. The reason behind this transformation heavily alludes to the demand for real-time consumer-brand interactions.  

Actionable data has been the missing piece of the puzzle between big data and business value in the past. But actionable data completely bridges the gap.

Unlike traditional bid datasets, fast data does not process on Hadoop and NoSQL databases to analyze information in batches. On the contrary, it processes data in real-time streams that enable data analysis in less than 1 millisecond. This flexes a business’s arms to take immediate action and create a nimble process. Moreover, it helps keep your consumers engaged with your brand as they continue to stream and interact with different content that your business has to offer them. 

This is the complete game-changer in your market analysis activity. It not only gives you powerful insights but ensures you can put them to use immediately. This means the quality of your data at scale is a huge success element of your overall simplification of this complex process. 

Final thoughts

Big data on any day is one of the foundational elements of any modern business transformation. Done right, it could open doors of opportunities to connect with your target audience and build the next business unicorn. However, everything falls back on how well you process those data. 

Your data becomes valuable only when you transform it successfully into information. The higher the quality of synthesis, the more actionable the insights, which would finally lead to higher-quality decision making. But here’s a word of caution. 

Although data is the oil of modern business, it still can’t capture the subtle nuances of dynamic human nature. Irrespective of the quantity and quality of data, understanding the pulse of your market is almost impossible without understanding your audience. This is why you need to keep your customer feedback loop open. 

Complementing each other, your customer feedback and big data analytics insights can support your product growth and improve your product-market fit. 

So now, when you know what to expect from the future of data analytics, which one of the above forecasts did you see coming?

Author bio: Atreyee Chowdhury works full-time as an Instructional Designer and is passionate about writing. She has helped many small and medium-scale businesses achieve their content marketing goals with her carefully crafted content that is both informative and engaging. She lives in Bangalore, India with her husband and parents. She loves to read, experiment with different cuisines, travel, and explore the latest content marketing and L&D trends in her free time. You can reach her on Linkedin

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