Perspectives 101

 The whole point of telling a good data story is to persuade your audience or stakeholders about your findings and the solutions you have to offer after analyzing the data. There are three main metrics that tell us how persuasive our story is: 1) How well explained the story is. 2) Whether the story enlightens the audience. 3) Whether the story engages the audience. Also a data story consists of three elements : 1) Data 2) Visuals 3) Narrative Note : 1) Data and narrative help to explain the situation. 2) Data and visualization help to enlighten our audience 3) Narrative and visualization help to engage our audience In a nutshell : Data Story = Data + Visuals + Narrative Data + Narrative = Explanation Data + Visualization = Enlighten  Narrative + Visualization = Engagement Data visualization considerations : 1) Choose the appropriate chart (eg : bar chart for categorical data, line chart for numeric data) 2) Focus on what's relevant 3) Choose the right colors Creatin...

 The 80/20 rule determines that eighty percent of the result comes from twenty percent of action/result. examples : 1) Eighty percent sales from twenty percent of clients. 2) Eighty percent work done in a company by twenty percent of employees. 3) Eighty percent wealth distributed in twenty percent population Therefore choose your twenty percent wisely. You should know why this blog is so short (it only contains the twenty percent)

 This article is from a data analytics perspective. Before getting started with the different data sources, let's talk about the different types of data that can be available to an organization: 1) First party data : Data that is directly collected by an organization about it's customers. 2) Second party data : Data that is collected from an organization that directly collects the data. 3) Third party data : Data that is collected from an organization that does not directly collect the data. The most common sources of digital data are : 1) Web server log : A server record of the interaction between a person and a website or app. 2) Cookie : Website specific piece of formatted text stored in the browser. 3) Pixel/tag : A small piece of code that instructs websites to send information to a third party. 4) SDK (Software developer kit) : A library of code that can easily be installed in an application to make certain functions easier. 5) API (Application programming interfa...

 Our personalities can be broadly categorized into four categories and we'll use the acronym OCEAN to elaborate on it. Before getting started let's talk about why we need to understand personalities at the very first place. Well it helps in predicting behavior oh other people, and getting to know yourself better, that's why. Our behavior is influenced by two main factors, personality and situation. Back to the OCEAN acronym. These are the big five personality traits of humans : O : Openness C : Conscientiousness E : Extroversion A : Agreeableness N : Neuroticism Let's talk about the big five in some detail. Openness : This trait is all about how an individual perceives new experience. Someone with high openness is likely to be open minded, enjoying change, future oriented. Someone with low openness is likely to be close minded, prefer things to stay as they are, past     oriented. Conscientiousness : Being dutiful and wishing to do one's work well is being con...

 Now here's a framework that's super helpful for data science projects. Before applying the framework, we must set the goals and objectives of our project. Goals should always be smart. S - Specific M - Measurable A - Attainable R - Relevant T - Time bound example : Gain 1000 subscribers for a new service in 5 months. Once the goal is set, we should figure out a key performance indicator (KPI) that will help us monitor our growth with respect to our initial goal. example : New Subscribers per month One the goal and KPI are determined, we can start to look at the OSEMN framework to kick off our project. O - Obtain data S - Scrub data E - Explore data M - Model data N - Interpret data Let's look at this framework in some detail. Obtain data : We have to obtain data to analyze it. In our example we can look at previous sales data to figure things out. data can be of 3 types : First party, second party, and third party. data can come from 5 main formats : txt, xlm, csv, json, ...

                                                           Hey there! Hope everything's going well.  Ever wondered what differentiates a successful product from an unsuccessful product? Although success is a subjective term, we are talking money (profits) here . Let's talk about the marketing process and observe a few awesome companies to address that question. The marketing process can be considered to be a four step process : 1) Objective → 2) Strategy → 3) Tactics → 4) Financials In this blog we will go step by step through this process and learn about each step in detail. Objective : We try to answer the question 'What are we trying to accomplish?'. That's literally all we do in the objective ...