Data is abundant—whether you’re tapping into it or not. Customers, employees, and operations are constantly generating data that organisations can harness to improve their business—and their bottom line.
Big data lets you analyse and use vast amounts of rich information streaming in live from many sources. One crucial way in which big data can help companies is innovation. “Innovation” isn’t just a buzzword—it’s what separates successful enterprises from failed ventures.
But innovating isn’t some abstract exercise. Here’s how big data can help companies innovate at every stage of their operations—whether it’s market research, product development, or getting a product to market—to gain an edge over the competition.
1. Better Market Research
Real-time big data analytics is the ultimate tool for market research, generating insights into customer demand, preferences, and behaviors that would be impossible to obtain using traditional data analysis.
Markets move constantly, and innovative businesses move with them. Big data can help you analyse large quantities of up-to-date market data and predict key growth areas. This means you can concentrate your development in the market segments with the greatest, most relevant customer demand.
Big data is unstructured and diverse, from all manner of sources, presenting valuable information that can drive your market research through faster, more detailed insights. Pulling data from web cookies, customer service interactions, social media, and other sources makes it possible to truly understand what your market desires.
Understanding the preferences of your individual customer segments in real time can help you develop innovative product ideas in response to the latest market signals.
2. Streamlined Decision-Making
Data drives decision-making in mature organisations. Harnessing big data analytics can help you to make quick, high-quality, evidence-based decisions.
Traditional data analytics involves batch processing, which is retrospective and limited to a defined data set. You can get much better insights from big data analysis, which occurs in real time, using a dynamic schema to analyse a diverse set of unstructured data.
Data visualization tools, such as Prometheus or Grafana, can help you make sense of data as it emerges. Using this data, you can make informed, confident judgments about your company’s direction of travel.
Big data also helps you monitor the impact of decisions and react as necessary. Taking a risky decision is no longer a gamble if you can see its effects and reverse course if necessary. This means you have more scope to make unconventional choices that your competitors might be unwilling to consider.
These benefits allow you to act swiftly and decisively—and innovate faster than your competitors.
3. Accelerated Product Development
At the development stage, big data helps you design innovative products based on a rich understanding of your customers’ needs and preferences. It can also help you speed up the product development process—a key factor in surpassing your competitors.
Big data analytics can enable you to gather and dig into customer feedback and usage data in real time. Research and development teams can implement the insights gleaned from such data into the product development process.
For example, a company creating mobile apps can draw upon insights from behavioral analytics software. This data can relate to hundreds of processes on many thousands of users’ devices, allowing product development teams to both quickly adapt existing products and develop new ones.
4. Increased Productivity
Business innovation isn’t just about ideas: It’s about being the first to deliver innovations to consumers. Big data analytics can offer massive productivity gains, enabling businesses to get their products to market faster.
You can make particularly significant productivity gains by employing big data analytics in tandem with other technologies, like 5G connectivity, AI, and the internet of things (IoT).
For example, enterprises can introduce high-definition cameras into their workspaces to study the environment using AI and identify new use cases on the fly. A factory camera might detect that boxes stacked in a certain way are more likely to lead to injury or damaged products. They can then link this data to other areas of automation and change how those boxes are stacked.
Minor improvements in the production process lead to huge gains in productivity at scale, enabling you to deliver your innovations to the marketplace more quickly and efficiently.
5. Proactive IT Optimisation
The machines you use in your workplace are constantly generating log data. For many years, businesses have been analysing this log data to gain insights into their operations. But big data analysis offers you the opportunity to truly harness this information to drive innovation and efficiency within your business.
Log data derived from containers, streaming sources, cloud environments, and virtual machines provides opportunities for swift resolution of issues and proactive monitoring of high-threat areas. But traditional data storage architecture isn’t suitable for analysing the rich and varied information provided by modern log data—this requires a modern, scalable, adaptable infrastructure. Log data doesn’t easily conform to the relational schema required by legacy databases—and many teams can end up trying to “boil the ocean” without getting the insights they need.
Improved ITOps and AI-powered monitoring can automatically scan and analyse log data from a variety of sources. This allows you to detect issues that might not have been spotted previously—and massively cuts the time spent on what have been manual data collection and analysis.
