Availability of connectivity coverage, advancement of tools and devices push the effort in digitalization of most of our activities. Sometimes, we get lost in enormous amount of data that we have whether from internal databases, surveys, sample collections or web crawling. This post will discuss about ideas on data usage mainly in retail business based on association rule mining although the rule itself is appropriate for a number of industries including bioinformatics, manufacturing, pricing, etc. We will go through the idea and implementation.

Simplified flow of data analysis. Understand the requirement. Defining the needs. Analyze the information. Interpret the result. Presenting the findings. Storytelling. Recommending solutions. — How to get start to work with data? What kind of data to adopt for solving your business problem? What tool is best suit to answer your question? …

As the field data science are evolving, machine learning and deep learning are gaining attention from the crowds. Are we forgetting the fundamental knowledge lying behind these sophisticated methods? We are tending to call a complex but powerful model, a black box model’, because it is losing interpretability as it gains the power to give final desired output, but we are losing track of the development and some insight beyond those data. So, let’s back to the basic about statistics, its importance should not be fading.

Time series analysis is applicable in numerous industry, such as business, economic, financial and even healthcare. Scientists were doing research on this topic since 19th century. As the name suggests it is highly dependent on point of time when it is collected. Have you ever thought of what make it a special kind of dataset and what makes it different from regression problem? — Time series is a collection of ordered data points collected sequentially over a period of time. Generally, it is collected at regular intervals. It is special as data points are not independent, we expect a certain degree of serial correlation. There are no independent variables and time-dependent make it distinct…

Density-Based Spatial Clustering Application with Noise (DBSCAN), an award-winning clustering algorithm that catches our eyes. Understanding what is DBSCAN and its application in customer segmentation, a critical area in business analytics. — Intro We always try to focus on a subset rather than broad coverage of potential customers to optimize our business objectives by shrinking our target customers through customers segmentation effort. Recall customer segmentation via centroid-based clustering — K-Means, discussed in previous post, there are some drawbacks associated with model applied…

Application of Multivariate Analysis and Classification on R. Forecasting profitability and enhancing sustainability through the weights and gender prediction by inspecting its physical size. — Intro Abalone is a type of marine snail with high nutrition values and economic values, almost whole abalone, including viscera and shell can be processed and serving as sources of income for fishing industry. High market demand for abalones has led to overexploitation, raising public’s concerns on environmental issues. Governments…

How do we define ‘churned customer’? How to initialize a churn model building process when you have unlabeled or unsupervised data? Defining ‘Churned’ for Unlabeled Dataset might be more challenging than building a supervised predicting model with acceptable accuracy. — Often, when we try to build a machine learning model for churn prediction, we are provided with supervised dataset where ‘churn customer’ are identified and labelled. Why does business implement subscription, membership and contract based business model? Besides information collection including personal details and transaction details, customers management and spending…

Traditionally, we used hard code a series of steps or procedures, input data, and program will output results. As machine learning evolves, we apply algorithm to learn from historical data and it tells the program what to do and how to complete the task. Can you see the sequence of intermediate actions are different? — Hard coding instruction may induce some limitations, we might miss some useful information or the thoughts are bounded. For instant, we are trying to find the rules to produce an accurate prediction for future events from the data available. The very first step in the process is asking yourself some…

Emphasizing customer retention as much as exploring new potential customers ensuring business sustainability and growth. Building a churn predicting model to identify underlying churning factors and customers inclining to leave. Choosing the right evaluation metrics helps to build more practically useful model. — Telecommunication industry has been showing exponential growth in line with rising demand following technology advancement. The competitions among services providers are so fierce that they are executing different strategies to meet the customers’ needs. Effort in retaining existing customers is now as important as searching for new customers.