Digital technology has made it easy for organisations to gather data about people and consumer behaviour. For example, when customers join a retail store’s loyalty program, they think they benefit from the deal. Every time customers buy products using their loyalty cards. Stores can track the products that they purchase. You can know which products your customers are usually interested in and target them accordingly. This is the potential of big data and data mining for businesses.
They are not just tech jargon but are used in the real world to increase a company’s profit. It sounds simple, but such processes rely on a huge amount of data and complicated algorithms to succeed. Vast volumes of data must be collected by thousands of customers and then analyzed for any patterns. A great deal of work goes into finding what your customers desire, but if you can find that with data, your business will grow at an unprecedented rate.
For the information to be processed accurately, you need to understand data mining and big data. You need to understand how they work, their benefits for your business, and the differences between the terms.
Data in the digital age
Big data has the potential to reshape the aspects of modern life. Shopping is just a part of the big picture. It can also be helpful in the healthcare sector. One such example would be the partnership between Mayo Clinic and Google. The partnership intends to store a huge amount of health data in Google’s cloud. After that, Mayo Clinic will use artificial intelligence to study the data and predict future diseases based on patient behaviour. This information is beneficial for everyone out there as it creates a relationship between two aspects, and you will know how to avoid certain diseases.
Big data is also changing the education system. Online courses have been popular for a long time, but Covid19 gave them a much-needed boost. Now universities offer degrees with completely remote education too, and soon this change will be seen in other universities too. Of course, nothing can replace college, but online courses help people upskill themself at any phase of life.
Course designers can track information like how long it takes students to answer a question or which course material users go back to more often. If they see that students go back to one material more than others, then they can make it easier to understand.
Big data and data mining help companies understand user behaviour, which helps you provide a better user experience.
Data is a big part of the digital age and the advancements that come with it. Your user information is mostly collected at every step for your advantage. Data can enhance all aspects of different industries, from medicine to education to commerce. Data is precious for companies as it helps them understand their potential customers or customers. That’s why many companies even pay to acquire data.
What is big data?
If you run a business, you may need to use big data. That’s why you should know that it is not just a fancy tech term and can benefit your business. Big data is characterized by its size. The datasets are so large that they need advanced computing technology to be analysed. Big data became popular around 1997, and then it was used to refer to data collections that were too large to be captured within an acceptable scope. In the next decade, the same term will be redefined many times. The concept we understand today is a bit different and is usually defined using the five V’s.
- Volume- Data has to be in large amounts for it to be called big data. The minimum requirement is one terabyte.
- Variety- Another trait of big data is that the data is collected from different sources like social media, the web, photos, and audio recordings.
- Velocity- Big data must increase at a rapidly growing rate.
- Veracity- The data must be accurate or trustworthy so that you can make decisions based on it.
- Value- Big data must be valuable. Large amounts of data can be collected but it’s worth nothing if it is not valuable for your business. Data science is about using techniques like data mining to discern the value and gain the benefit from the data.
Benefits of big data
Most businesses can gain several benefits by utilizing big data.
Customer acquisition and retention
The digital footprint of your customers reveals critical information like preferences, needs, purchase behaviour, etc. Businesses can use these data patterns to tailor their products or services to each consumer. If you do this, you will ensure customer satisfaction and retention. It will ensure that sales increase, and if they are not increasing, they will not drop.
Amazon uses big data to offer each user the most personalized shopping experience. What the store looks like and the suggestions are made using big data.
Big data allows companies to target products to consumers who are more likely to spend money on such products. With the help of big data, companies are saving tons of money on marketing campaigns. Big data helps companies analyze customer trends by monitoring online shopping patterns and point-of-sale transactions. These insights can be used to create ultimate marketing campaigns which promote products to people who may need them. This improves the efficiency of marketing campaigns and provides a better return on interest.
Running a business can be risky, so you need risk management solutions to address these problems. Big data plays a big part in developing risk management strategies and solutions. You can identify the risks by optimizing complex decisions for unexpected events.
You can gain a lot of insights with the help of big data and utilize them to innovate in your business. Big data allows you to keep moving forward with time and not be stuck in one place. The large volume of data will help you understand what your customers appreciate. Use this information when a new product is in development. You can also use these insights to create a long-term business strategy, be flexible, optimize customer service, improve marketing tactics, and increase employee productivity.
In today’s competitive business landscape, it is necessary for you to be able to track product reviews, and product success and monitor your competitors. This helps you analyze if your products are left behind the competing products and if they are you can provide a compelling upgrade.
Complex supplier networks
Suppliers can apply big data analytics to eliminate the constraints they usually face. This allows suppliers to use a high level of contextual intelligence which has become a critical success factor. The insights you gain about your business will be accurate!
One of the significant benefits of big data analytics tools like Hadoop is the cost advantages for storing, processing, and analyzing large amounts of data. A great example of cost optimization in big data is the logistics industry.
Usually, the cost of returns is 1.5 times higher than usual shipping costs. Companies use big data to minimize product return costs so that customers order products they will not want to return. This reduces the chance of product returns.
Data science helps you serve customers. Customers always leave behind their behaviour and feedback, no matter which business they run. Customers leave large amounts of data which can be converted into insights by mining big data. Meaningful patterns are then formed, which can provide you with insights. How you use these insights is totally up to you. They can be used to develop a new product, improve customer experience, improve operational efficiency, etc.
Data mining-type tools are being used to automate routine processes and tasks. This frees up the time of employees, which they can use on tasks which require some thought.
What is data mining?
Without big data, there is no process like data mining because mining big data is a process by which companies study information to gain precious insights about consumer behaviour. Every modern industry in the digital age relies on mining big data in some way, affecting consumer behaviour too. Data mining is about finding meaning in huge volumes of data. Most businesses store data even when no one is paying attention. When a customer purchases something at a shopping store, they will collect customer data. It is up to you to find interesting patterns with that data. This can only be done by mining big data.
Big data deals with pre-programmed algorithms that can sort out user data into an excel table. Analysts with vast knowledge of data science need to examine the raw data. However, it is impossible to gain any insight when the volume of the data is huge.
Data scientists use algorithms to find out patterns, reveal the key points, and the actionable insight. For example, if the data suggests that people buy more products on Friday, then you can promote a Friday sale in your store.
The data scientists can communicate the insights to a business’s marketing team and use them to create a strategy. Using big data and data mining in most operations and promotional efforts is necessary for the success of your business. With the help of big data analysis, you can even predict customer behaviour. Isn’t that what most business owners want? You can mitigate the risks by following the prediction.
Most companies just use data mining to learn more about their target audience and their needs. If you are able to understand your target audience and fulfil their needs with your product, then success is a guarantee. This is why businesses invest in big data and data mining. However, there are other uses of data mining in business, like improving a business’s overall operational efficiency by providing key business insights.
Data science is incredibly useful for a business irrespective of the industry size and competition. Organizations can only go on functioning with mining big data as their daily operations rely on it. Now, it is up to them whether they outsource this task or hire a data science expert. Big data analysts are in high demand because they are skilled in generating insights from big data. These big data type skills are in high demand because every business is in need of data analysts.
Q1 What are some of the best big data tools?
The job of big data tools is to bring order into the chaos of raw data. Some tools are better at this task when compared to others. Here are some of the tools that you should consider using.
- Apache Hadoop
- Apache Spark
- Apache Flink
- Google Cloud Platform
Q2 What is the difference between data mining and data warehousing?
The end goal of data mining is to gain some insight from the data. In comparison, the end goal of data warehousing is to create a collection of related data that can be retrieved and analyzed to gain insights. Data warehousing is necessary before data mining can take place as gaining insight just from data warehousing is next to impossible.
Q3 What is data purging?
Data purging is a process which takes place in database management systems to ensure that relevant data stays in the database. The process cleans junk data by eliminating unnecessary rows and columns with NULL or duplicate values. To maintain the quality of a database, you have to purge data that is irrelevant anymore. Junk data takes up a lot of space in the database, which slows down the database. Processes like data purging ensure that the results produced by data mining are optimized.