Analyst in Action

Let's start today's blog with some questions. Are you greatly indulge in creating data visualization? Do you want to come up with scenarios that aren't available in the data? If yes then this is the blog you really want to read. Parameters allow you to create features or scenarios which help the user to control the data in a much better way. You must be wondering how the users get a better control so mainly parameters allow the user to test different what-if scenarios that aren't available in the dataset. It is like some value that helps you to tailor your visualization according to the dataset. Options where you can use parameters in tableau- use it with calculated field or you can use it by combining with sets. We will look at both aspects in this blog. We can make the parameters more interactive and intuitive in nature by using parameter actions that allow users to change the value just by a click As mentioned, we are considering two basic aspects for creating parame

Source Have you wondered how to improve organizational efficiency? There is a pool of options that can help you out in achieving it. Let's talk about one of the most important ways i.e. ERP system (Enterprise Resource Planning). Why every important thing sounds so weird? ERP is like one of your friends which acts as a gel between all friends. To be more specific ERP system is like a bridge that helps in connecting all critical departments. ERP software allows all departments to collaborate and operates on a common database. All departments have access to the dataset which signifies the performance of the company. In the modern world where every organization is getting flooded with vast data, the role of BI is very pivotal. Mainly every ERP system has a built-in BI feature but in some cases, if you receive a large number of datasets on daily basis then you need a specialized BI tool that can be integrated with the ERP system. It can help your organization to get better insights from

Source You must be aware of various customer segmentation techniques and analyses. Let's discuss one of the most important analyses today i.e. RFM Segmentation. What is this 3 letter term can do? The answer is it can do wonders let's get to know more about it. RFM analyses are the method of separating your customers based on RFM scores which will help you in identifying your best customers and lost customers. RFM is an acronym for Recency, Frequency, and Monetary. The main idea behind this analysis is to understand your customers well because it will separate your customers based on how recently your customer made any purchase, how often they are buying, and what is the average cost of their orders. RFM analyses can be performed in various analytical and programming tools such as Python, R, and Excel. I have done it in Excel on sample data. How to do it in Excel?   Select the right data and insert a pivot table and select the pivot table field accordingly in my case I have se

Want to retain your customers then you are at the right place. It can be achieved by Cohort Analysis but the question is how this analysis helps in achieving it. Let's get started by understanding it. Cohort Analysis is used by the analyst to determine the user engagement of customers over time. To be more precise it helps to know whether our user engagement is increasing or decreasing over a period of time. It is done to know the level of user engagement and the customer churning rate in any organization.  In marketing, the cohort is referred to as the group which possesses similar characteristics or traits, and this analysis helps us to divide customers based on their behavior. To get a better understanding of your audience you need to perform such analysis on regular basis. It can be performed in almost every analytical tool mostly organizations prefer Google Analytics but I have done it in Tableau.  This analysis is done in Tableau. Let me walk through it and explain what it im

Have you heard of EDA? Let's, deep dive into Exploratory data analysis (EDA). It is the analysis used by a data scientist to spot the patterns, trends, and hypotheses to manipulate the data for getting your questions answered. It is a vital step to get the most out of any data and also it is critical because it provides a better picture of the relationship between different variables. EDA is mainly practiced to get a better understanding of your data before making any assumptions. It answers some basic questions related to data such as the confidence interval, standard deviation, and relationship that exist between different variables. EDA is a soul for any data analysis. According to John Tukey “ Exploratory data analysis is an attitude, a state of flexibility, a willingness to look for those things that we believe are not there, as well as those we believe to be there. ” Source There are mainly 4 types of EDA- Univariate non-graphical- It only deals with a single variable so it i

  Source SQL (Structured Query Language) plays a pivotal role in data analysis. The main purpose to create SQL is to help in managing data stored in Relational Database Management System (RDBMS). In elementary terms, it is the language that is used to interact with the database. You must be aware of the RDBMS which uses SQL extensively such as Microsoft SQL Server, Access, Oracle. SQL and SQL lite both follow the RDBMS model. Let's check out where these two differ. So let's understand what is SQLite ? SQLite act as a library for software. As compared to SQL it does not require any server to function. Generally, RDBMS requires a server to function. SQLite functions by combining the database to the application. The application help in interacting with the database. There is this term " self-contained " which is associated with SQLite which means it can operate on its own without the support of the operating system. This feature is the highlight of SQLite and makes it av

Source Want to improve your business performance? You heard it right it can be achieved by implementing Business Intelligence tools in your business operations and utilize  big data  in effective decision making. Business Intelligence is a process that can help executives and managers to make informed decisions by analyzing data and by developing actionable insights out of it. It is one of the major concepts which can help your business grow.  There are several Business Intelligence tools available it all depends on your needs. Tableau, Microsoft Power BI, SQL, QlikView, and many more. All of them perform in a similar way but there are minute differences between them when it comes to their functionality. SAS ( SAS BI ): Business Intelligence: It is a great business intelligence platform that also offers advanced predictive analytics which can help to predict future business trends. There are several APIs offered by SAS to customize your analysis and reporting. QlikSense ( Qlik BI ): It

  Source Today, every electronic device is a source point to some sort of data. In the era of big data, you need certain tools to uncover the story behind those mere numbers. Business Intelligence and analytical tools make our life easier in devising actionable insights. When I started my analyst journey I was introduced to R Programming which comes under the umbrella of data analysis and later on I shifted to Tableau and SQL. I have worked more with BI but I won't let BA loose in this data battle. This blog mainly highlights the difference between Business Analytical tools and Business Intelligence tools. Both of them perform in a similar manner but they are different in functionality. Business Intelligence (BI) is a much wider category which includes Business Analytics (BA) and Data Analytics but overall all of them are data management systems. The very basic difference between them is BI focuses on descriptive analytics while BA focuses on predictive analytics. Descriptive analy