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9 Benefits of Automation in Data Mining Process

When retailers want to wean away customers from competitors, they must entice them with customized coupons. And to tailor personalized coupons, it’s important to understand a customer’s individual purchase history. The history must be analyzed to discover the products they prefer buying and the promotions that they would likely be interested in. But how do you get access to this information from an alien domain. By scraping information from their website. And the easiest and safest way to scoop data from your competitors website is through automated data mining


What Is Data Mining


We live in the age of massive data production. Every service or gadget we use generates a lot of information, and some of which like Facebook runs into hundreds of terabytes each day. All this data is a treasure mine of information which we can use to make a better product or deliver more efficient services. This process of collecting and analysing data to make sense of it is called Data Mining.


Automation Fuels Digital Transformation


Digital transformation is the process of transforming a business with advanced technology to improve efficiency and revenue streams. Unlike an isolated IT project like moving processes to the cloud, it consists of a combination of projects that transforms every component of your business to be digital-first. Among all the technologies involved, automation has proved to be the springboard for launching digital transformation initiatives.


Automation is the most critical step towards digitalization because when implemented end-to-end the entire team benefits from an improved, transparent and time saving workflow. Automating routine day-to-day workflows lies at the heart of successful digital transformation because it drives productivity, improves security, makes your process more compliant, flexible and scalable. 


Benefits of Automation in Data Mining


1) Automation Reduces Costs


Automation is the most viable option for business owners to save on costs. The biggest way of realizing cost savings through automation is reduction of employee hours. Automation has obviated the need to have an entire assembly line of people in manufacturing units because these tasks can now be done more quickly and less expensively. Further, automation has helped to streamline processes within a business. This has helped to identify and eliminate inefficiencies within the business resulting in cost savings. These asides, automation can be used to reduce incidental costs associated with a business process like eliminating the need to send physical invoices through mail service and replacing it with automated delivery of invoices through email. 


2) Increases Data Quality


Automation can recognise and take action on different types of data thus helping improve the overall quality of data generated. For example, an automated tool can recognise an email, address, credit card number, social security number to validate an entry or flag a compliance issue. This feature when put to use in a mortgage process can help to identify data inconsistencies and thereby spot errors or frauds. Likewise, automated data processing can help credit card departments match data to find out candidates eligible for credit cards.  Automation tools come equipped with advanced data profiling capabilities that can assess core data attributes to identify format, structure,  and other key characteristics. This feature helps in sorting data effectively and in the process improve data quality.


3) Scalability of Operations


As businesses grow they need to process orders at a scale that is far higher than human capability. This is an area where automation comes very handy. Automation scales up with a business and automatically allocates workload to the right department. For example, automating a fashion website, can help send the list of clothes ordered by a customer to appropriate departments. As a result it frees up time for the employees and sends packages out faster. It’s primarily because of end-to-end automated processing that Amazon has acquired the speed and accuracy needed to become a lead market player. This can be particularly helpful during seasonal business activity when there is a need to hire more workers. 


4) More Data Deeper Insights


Data insights refer to the understanding of a particular business phenomenon by analyzing incoming data streams. These insights allow users to understand the “behind the scenes,” developments, understanding which is very important for highly regulated industries like banking and healthcare. Likewise retail companies want insights for product recommendations or understand customers propensity to churn. Automation helps to understand and communicate meaningful insights with the right kind of data visualization and presentations for better understanding.  Once the value is  uncovered automatically it leads to improved and fast business decision-making.


5) Intelligent and Data Driven Decisions


Automated data insights can tell the likelihood of a customer to churn. When drilled down it can reveal the factors that drive churn rates. This allows decision-makers to make changes to business strategies and processes. When done regularly it translates to real business value in the form of right and timely decision making.  Data driven decisions for instance can help retailers determine what new items to introduce and which store locations need them the most.  Likewise, it can help the hospitality sector identify the key reasons for key fluctuations in demand for rooms and services or the food and beverages industry analyze customer foot fall in real-time and plan ahead and stock up menu items in demand. 


6) Real Time and Near Real Time Process


Some businesses need solutions that can process large volumes of data for prescriptive and predictive recommendations in real-time. For instance, those looking to travel or purchase a vehicle, want the best deal. Automated data mining can make this happen in real time by scraping data off websites, comparing it and showing the best deal. Businesses too can leverage automated data mining techniques to make decisions on the production line in real time, get timely information about allocated and de-allocated car spaces in real time, handle thousands of financial transactions between individuals and businesses in real time and so on. By automating processes that require laser-sharp precision, businesses can lower labour costs, reduce production waste and optimize yield significantly.


7) Free Up Time


Data management automation lends unprecedented speed and accuracy to processes which in turn leads to significant time savings. For instance, few time consuming marketing processes like booking an appointment, qualifying cold leads and prospects, and customers on boarding can be automated and the overall time needed to carry out these processes can be reduced by one tenth the usual time.  Similarly an ecommerce company can automate processes like product launches, communication based on customer purchase behaviour, abandoned cart email sequences, communication with suppliers etc. With businesses being freed up with more time focusing on money-making or other productive tasks becomes a lot easier. 


8) Increase Productivity


Automation can lead to big productivity gains. The productivity gained in an IT organization can be a good example to discuss. Centralized ticketing, reporting, and logging obviates the need for an administrator to notice an issue and act. Issues are addressed no sooner they arise, keeping backlogs at bay and maintaining optimum efficiency levels. Automation also helps IT engineers track recurring issues with customers and address them proactively. Likewise in mortgage operations lenders need not wait for days to establish the financial credentials of borrowers. Automated data mining fetches all financial information in just a few seconds thus helping the underwriter to arrive at an early decision. 


9) Increase Operational Efficiency


Operational efficiency is a metric that measures profits earned over operating costs. And operational efficiency is determined by workflow. If the workflow is dependent largely on siloed and legacy systems, paper-based forms and excel spreadsheets, then it becomes more human-dependent, time consuming and error prone. The cumulative effect of this is reduced efficiency. As automation, streamlines workflow and removes human dependency operational efficiency takes a quantum leap. It empowers businesses to do more with less and equips them with a competitive edge as they can deliver high quality products or services to customers more cost-effectively. For financial institutions the jump in efficiency comes with reduced risks. 




Automated data mining techniques help data scientists execute tests for scenarios that they could not have done before. Also, it allows them to experiment with more use cases as it reduces the time taken to come to a conclusion. In the world of data science, automation is a game-changer and promises a lot more than we can imagine.

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