According to a recent statement by renowned SAS author Philip Russom, one of the definitions for the term “big data” is based on the 3Vs: volume, variety, and velocity. The latest research on big data and its impact on business backs this up with some interesting findings.
What Is Big Data and Why Is It Important Today?
The term “big data” refers to a large and diverse amount of data that is difficult to gather and analyze with traditional methods. Big data is more than just large storage of data, and it has more relevant attributes, such as data variety and data velocity (speed). Big data’s importance is based on its usage rather than its size.
Companies can structure big data into different datasets, or it can be unstructured, which is the data you find on the internet and social media platforms. This data is collected by companies and institutions and is analyzed to gain insight into areas such as customer demand.
Companies gather data information from various sources to structure their strategies. Big data is incredibly valuable for any business. Managed correctly, this data can help a business be profitable and provide relevant solutions to its audience.
Advantages and Disadvantages of Big Data
Big data allows businesses to do many things. Companies can detect errors in real-time, discover insightful information from large industries, analyze consumer behavior, develop new product projects, manage cost reductions, increase productivity, track potential customers and clients, among other advantages.
Big data technology, however, is overwhelming and can create an overload. Because of the huge amount of data available on the internet, finding and collecting useful data for your business can be tough and require expertise.
How to Use Big Data Information
Collecting big data isn’t difficult. However, it can be hard to gather relevant data from a wide variety of sources, store and analyze it properly to reveal the relevant insights needed by the company. Once the company gets the data, they need to structure a big data strategy, recognize the sources of this data (web or social media platforms), store, and analyze it.
Nowadays, there are experts, such as data analysts, who specialize in this complex analysis and can make decisions derived from the collected data.
Big Data for Small Businesses and Startups
Digital transformation has allowed the business world to grow faster, be more flexible, and be more profitable than ever. The immersion of big data into business has revolutionized business models. Startups can differentiate themselves by simply using the appropriate tools and adopting solutions that can help them generate actionable insights and quickly become a strong player in the market.
Big data science can play an important role in a startup’s operation. Insights can help build a marketing plan and build reliable customer service. Big data analytics can be useful for small businesses to launch their product in the market. Also, big data can potentially help any startup achieve a fair return on investment.
Big Data Information for Competitors
Startup companies should use efficient big data sources to map out their competitors. Companies publish their annual and quarterly reports based on their financial performance and customer feedback. You can find out competitors’ products and service characteristics, identify their target market, and retrieve information from social media and forums based on their products’ quality.
By collecting competitor’s data, startups can analyze information and make the right decisions for their business. With the help of artificial intelligence, data analysts can identify relevant and important information for small or big businesses.
Big Data Information for Consumers
Startups use big data information to identify consumer behavior and discover products and services based on market demand. Startups can use big data to build customer loyalty, sustain growth, achieve a competitive advantage, and establish their position in the market. Big data analytics can assist small businesses in following the customer journey, engaging with the target audience, and understanding the customer experience.
Big Data Startups Today
Big data startups today are mostly focused on analytics, cloud solutions, artificial intelligence software, cyber-security operations, data mining, and data science. An example of a big data enterprise is the real-time data analytics platform MemSQL startup, based in New York.