Big data is large, complex, and rapidly generated data sets that can be transmitted from many sources.
Nearly every industry uses big data analytics to identify trends and answer questions, solve complex problems, and gain insight into customers. Organizations and companies use the information for many reasons, including to grow their businesses, understand customer decisions, enhance research, make forecasts, and target key audiences for advertising.
There are three types of big data:
- Structured Data: Unified data. Structured data can be described as an Excel spreadsheet that contains fields such as “item purchased,” price, date and time, and “payment method used”. The data is sorted into the appropriate columns.
- Unstructured Data: Unstructured Data lacks the rigidity of structured data. Many fields don’t demarcate meaning. Data can be in any format, including text files and audio, as well as imagery. Thanks to machine learning-powered tools and artificial intelligence (AI), businesses have recently been able to make sense of unstructured data.
- Semi-structured data: Semi-structured data includes some structured field data. It is, however, so complex that it requires significant computing power to understand the data.
Data is constantly generated whenever we open an application, search Google, play on an online casino platform, or simply move from one place to another with our mobile phones. Companies and organizations can store, visualize, analyze, and manage a huge amount of information.
This complexity and volume are beyond what traditional data tools can handle, so there have been a number of specialized big-data software platforms as well as architecture solutions to handle the load.
Big Data: The Benefits
Although big data can seem overwhelming due to its large scale, professionals can still benefit from the wealth of information available. Big data can be used to discover patterns in their sources and provide insights that will help improve business efficiency and predict future business outcomes.
How big data is used
Big data is complex because of its diversity. Systems must be able to process these different semantic and structural differences.
Special NoSQL databases are required to store big data in a way that does not require strict adherence to a specific model. This allows you to combine disparate information sources to get a comprehensive view of what is happening and how you should act.
Usages in finance
Financial and insurance use big data for predictive analytics, fraud detection, risk assessment, credit rankings, brokerage, and other uses.
Big data is also being used by financial institutions to improve their cybersecurity and personalize financial decisions.
Customer Response Analysis
Big data is full of customer feedback, reviews, comments, and feedback. There are many customer communication channels, including social media and product review forums. It is crucial for companies to analyze and understand what customers think about their products or services in order to improve customer satisfaction. Analysis of customer sentiments can be done using big data and social media channels. This gives companies a clear picture of what they should do to surpass their competition.
Understanding customer behavior is the key to big data’s potential. Businesses are able to harness the power of big data through behavioral analysis to bring great value to their customers. The value of behavioral analytics has been tenfold for organizations that use it to predict customer behavior.
Companies must target customers effectively to increase customer acquisition. This is because of increasing customer acquisition costs. Information about a customer can come from many sources, including transactional data and social media. To reduce customer acquisition costs, organizations can correlate customers’ purchase history and their profile information on social media. They then target customers with customized offers they are interested in. Big data analytics has helped companies reduce their customer acquisition costs by up to 30%.
Organizations in all industries face the most common problems: financial crimes, fraud claims, and data breaches. Before big data analytics, fraud detection and prevention were a problem that affected all industries. Organizations can use big data analytics to detect, prevent, and eliminate all types of fraud. The analysis algorithms can detect unusual behavior patterns in card transactions and alert banks if a debit card or credit card is stolen. Banks can temporarily block any additional transactions from the card until they get in touch with the owner.
Improving your marketing
Data is the key to behavioral analytics, which is the science of understanding why people behave in a certain way. This data will help you identify where potential customers are leaving your sales funnel so that you can make improvements to increase sales leads, identify what is working and what isn’t, and fix any problems.
Reasons small businesses should embrace big data
Many business owners are unaware of the amount of data that their businesses generate. These data contain crucial information that can help you increase sales and motivate your team to increase cash flow and customer retention.
You can have a real advantage over your competition if you can capture and store valuable data and then learn how to analyze it properly.
Risks associated with big data
Security and privacy concerns are growing as more companies rely upon data collection and analysis for growth and differentiation from their competitors.
- Data breaches are a growing concern. You could face stiff penalties and lose customers. It is crucial to protect consumer data.
- Reduces anonymity. Large data is often analyzed in the round in large data pools. Your database may contain large amounts of data that could make it possible for many users to be identified, thus removing any privacy.
- Big Data may not provide accurate information. Big data is not a science. You might bombard a customer with targeted marketing to get them to buy, but big data may not reflect their true intentions.
- Mishandling data can lead to government sanctions. The penalties for this are severe. If companies mishandle data, they could face fines or class-action lawsuits.
The bottom line on big data
In the age of software subscriptions and AI, machine learning, and no-code data analysis tools, big data is a hot topic for small businesses. You should follow the big data trend and your competition will soon be able to benefit from it.
Founder Dinis Guarda
IntelligentHQ Your New Business Network.
IntelligentHQ is a Business network and an expert source for finance, capital markets and intelligence for thousands of global business professionals, startups, and companies.
We exist at the point of intersection between technology, social media, finance and innovation.
IntelligentHQ leverages innovation and scale of social digital technology, analytics, news and distribution to create an unparalleled, full digital medium and social business network spectrum.
IntelligentHQ is working hard, to become a trusted, and indispensable source of business news and analytics, within financial services and its associated supply chains and ecosystems.