It is impossible to disregard the importance of big data in today's business world. It has become one of the most valued tools to address business problems and reach higher goals. So relevant technologies that some of the biggest companies work with big data. For example, IBM, Microsoft, and Google, have it as part of their business strategy.
You can see the significance of big data when looking at the global big data market. Statista expects growth to 103 billion U.S. dollars by 2027, almost double its expected market size in 2020. The global Big Data and Business Analytics market has even more significant numbers, going from 169 billion U.S. dollars in 2018 to 274 billion U.S. dollars in 2022, with a five-year compound annual growth rate (CAGR) of 13.2 percent.
What is Big Data?
As the word itself describes it, big data is a massive amount of data. More specifically, collections of numbers or values are so large and complex that traditional data management and processing applications can't work with them. The usage and popularity of big data grew with technology, the Internet of Things, and mobile devices because it increased the amount of available data tremendously.
To deal with advanced analytics, companies are hiring data engineers to analyze big data and conduct predictive analytics.
The ability to access such an enormous volume of data can be positive or negative; it eventually depends on the organization and how well you filter relevant information out of the data mass.
Big data has specific characteristics that you can address as the 3 or 5 V’s. The traditional three V’s are:
- Volume: refers to the massive amount of data that is received. For some companies, this might be tens of terabytes of data and for hundreds of petabytes.
- Variety: describes the diversity of data. Many different data types exist, such as images, conversations, audio, videos, etc.
- Velocity: represents the speed of data generation. Some data you process in real-time, some can take longer.
And the extra V’s
- Veracity: describes the quality and the credibility of data. Due to the huge amount of data, it is important to have authentic information.
- Value: refers to the importance of the data. Businesses depend on relevant information, but not all data is equally important. A good question to ask is if the data adds value to the company or not.
Problems with Big Data
A large amount of data itself is excellent, but problems arise with that data's organization. First, a lot of data means a lot of noise, including information that is not valuable or irrelevant. Moreover, real-time data is vital to stay ahead of the game.
Still, it takes time to structure and organize the essential information from the unorganized data amount, which creates a dilemma. Companies often get confused about which leads to follow and which data is the most valuable to them.
The problem is that you have to put in perspective industry trends and future developments all the information gained from the data. Due to the complexity of this process, many companies outsource this process, which usually does not offer a cost advantage.
Why is Big Data analytics important?
Big data is not about the data itself; it is about examining it and uncovering disorganized information. Big data analytics is important because it helps businesses gain new insights, lay open patterns, discover correlations, or reveal market trends and customer preferences. It helps companies to create a differentiation strategy to better fulfill their target market, it creates a sustainable competitive advantage.
It would not be possible with "just" unorganized extensive data; it only becomes possible through analysts who look at the relationship between different types of data and filter and structure it. The idea of big data analytics is not new; it has been around even before the term "big data" existed.
Companies tried to collect their information and organize it to gain value from it. However, today, the sizes of data sets offer the possibility to collect and structure significant information manually; therefore, today's big data analytic technologies are essential and offer many benefits. Here are three main advantages:
1. Work efficiently:
Big data analytics make it possible to receive information faster and more organized than data has ever been before. This advantage saves time and long working periods.
2. Reduce cost:
The amount of data out there is unlimited, costly to organize. The right big data analytic technologies, however, reduce the cost by providing relevant information.
3. More awareness:
Since a lot of time and cost goes into filtering the needed information out of the amount of raw data, you can lose a lot of opportunities. Good analytics, however, create deeper and better insights into client’s needs and behavior, which results in a high level of satisfaction and repeat business.
Those three factors can create a substantial competitive advantage. Conversely, companies who disregard the importance of organized data miss out on valuable business insides that can mean lost opportunities.
How to Find Opportunities?
Every success-thriving business constantly searches for chances of advancement. Opportunities to become better, gain more clients, increase revenue or build partnerships. Keeping your eyes open and actively searching for improvements is not just what helps your company grow but also what separates you from your competitors.
Amazon, for instance, just bought the Australien startup Selz to use it as a third-party seller. This move helps Amazon satisfy their customers and contribute to increased revenue, as many other third-party sellers do. Interestingly, Amazon also took this step to stay ahead of its potential competitor Spotify. This case is just one example of many that prove how essential it is to constantly improve and innovate your business.
One company that uses big data analytics to create chances and competitive advantage are Innovation Intelligence. Without long searches, its business intelligence system gives you high-quality data insights into startups, investment, and partnership opportunities. The platform tailors every opportunity precisely to your goals or desired improvements, gives you detailed, up-to-date information, and makes your work efficient every step of the way — everything you need to bring your company forward.
Big Data Analytics is the Key for Opportunities
While big data can be complicated, the benefits big data analytics offers are winning. For example, the Innovation Intelligence platform will simplify your work process while saving you time and money. We collect data from startups and emerging technology companies, and organize it to you with artificial intelligence. For more knowledge about innovative business decisions through big data analytics, check out our innovation search algorithm.