5 Data Mining Techniques Businesses Need To Know About

With information flowing in from a number of sources — websites, mobiles, social media, and other digital channels, organizations are swarmed with volumes of data today. But the question that continues to remain unanswered, is how businesses can make use of this data. The answer lies in data mining.

Let’s take a look at the five data mining techniques that can help businesses garner actionable insights from all the data.

1) Classification analysis: Data is classified into different sets in order to reach an accurate analysis or prediction. An example of application of classification analysis is when banks try to determine who should be offered a loan.

Applying classification analysis to the database, they can define the predictors — annual income, age etc. and the predictor attributes — numerical values corresponding to the predictors. Using IF/THEN analysis, they can then decide whether someone qualifies for the loan. For example, if the age is more than 20 years and income is equal to or more than Rs. 50000 per month, they qualify for the loan.

2) Association Rule Learning: By far the largest application of association rule learning has been in forecasting customer behavior. This is because the technique helps identify relationships between different variables and establish hidden patterns in the data. This data mining technique is widely used for analyzing sales transactions.

An example of association rule learning in an industry like online retail could be — A user who buys product ‘A’ and also product ‘B’, is likely to buy product ‘C’ for a consequent need.

3) Anomaly or Outlier Detection: This techniques digs into the outliers in a data set. Outliers/anomalies are patterns that do not match expected behavior. When an event that does not conform to a predefined pattern occurs, data analysts categorize this as noise and remove it from the remaining data set. Also, when outliers are detected analysts try to find out what caused the disturbance in the expected patterns. System health monitoring and fault detection are two applications of outlier detection.

4) Clustering Analysis: In this technique, data objects are grouped in clusters on the basis of similarity. The idea is to group data objects in such a manner that the degree of association is maximal within each cluster and minimal outside it. For instance, clusters of symptoms such as paranoia, schizophrenia etc. need to be correctly diagnosed in psychiatry, for the right therapy to be started.

5) Regression Analysis: In this type of analysis technique, there is a response variable and one or more than one predictor. The predictor variable(s) are independent and the responsive is dependent. The technique is used for studying how changing the value of predictor can alter the value of responsive variables. Note that only altering the predictor values can change the values for responsive, and this is not true vice-versa. Regression analysis is being used since long as a forecasting technique, and to study causal relationships.

In businesses, regression analysis can be used to predict events yet to occur. Insurance companies, for example, use regression analysis to find out how many people will be victims of theft.

Optimizing business processes is another application of regression analysis. For example, a company might want to understand and optimize the wait time of a customer call and the number of successful sales, to find out what should be the optimum wait time for a client call to be answered.

Each of the five discussed data mining techniques can help businesses gain valuable insights from data and use it solve tough business problems. Converting raw data into knowledge is the key to making better, smarter, and informed decisions.


The Impact of Digitization: How HR Will Change

Balaji Panigrahy- HR

The human resources departments are usually packed with activity. From understanding the resource needs of a business to connecting and finding the right

A typical human resources department is a frenzy of activities. From understanding the needs of a business to connecting with and finding the right resources to fulfil them, the department has a lot on their hands at any given point of time.

But today, a new world of HR technology and design teams is on the horizon of growth. Modern technologies like mobile, cloud computing and more are now enabling HR leader to not just revolutionize hiring, but also improve the employee experience.

How digitization will change HR

Employee experience  

The current HR processes are mostly based on system records with web browser access, paper form to web form and transaction system based on process design of a business. But with digitization, HR will become an integrated platform using mobile apps, cloud based applications, real time analytics, employee dashboards and more, to create a human centered experience driven design.

Goal driven approach

The HR can now think of a way to make people and technology work towards achieving business goals in a more effective manner. By bringing together social, mobile, analytics and cloud technologies (SMAC), the HR can use the platform to develop apps that keep employees engaged and help them work towards the end goal, mitigating all the risks in between.

Efficient hiring

Digitization of HR will enable professionals to dig deeper into the talent pool from across the world. Using smarter apps and data analysing tools, the HR can look for specific skill sets in the desired fields and connect with them almost instantly. The modernization of the approach is sure to reduce the hiring cycle for businesses.

Employee satisfaction

The HR process – from hire to retire, plan to source, acquire to onboard, performance monitoring to rewarding employees, assessing productivity to developing effective strategies, will all be simplified with digitization. With modern technology the HR can dig deeper into employee analytics apart from general demographics to understand how they work, how they can be encouraged to perform better and what roles they are the best suited for.  

Decentralisation of HR

With the latest technologies, businesses can expand their HR teams to multiple locations and access a global talent pool for hiring.  The staff can work over a secure, uninterrupted and integrated platform from anywhere, anytime, making it easier to collaborate with the in-house team. With remote working becoming a trend amongst the millennials, digitization is a welcome change to HR.

How can businesses get started

Instead of resorting to traditional HR processes, businesses should change management to Digital HR.

By using modern technology, all processes can now be made on a workflow basis. This will ensure that employees can continue working in an effective manner, without having to reach out to the HR and awaiting a response.

While digitization will surely cut down on the role of the human resources department by automating redundant processes, businesses will still need professionals to manage some aspects of real employee engagement. Simply put, HR shared services and HR staff will need to be moved towards transformation.