Mwangome Erick’s Post

Data validation as a data analyst can be a mix of boring and interesting. It's boring either when there's too much work or when you're stuck. The fun part? It gets interesting when you figure out what went wrong. #DataValidation #DataAnalytics #DataInsights #Storiesaboutdata

🚀 A data analyst: ✅ Builds dashboards ✅ Provides data to partners ✅ Delivers results quickly 🔥 An amazing data analyst: ✅ Asks WHY before dashboard building ✅ Grasps business impact ✅ Seeks stakeholder feedback early ✅ Provides comprehensive documentation ✅ Writes high-quality code with best practices #dataanalyst #analytics #dataanalytics

Essential skills for Business Analyst are divided into 2 categories; Technical Skills * Querying Data with SQL * Data Exploration and Analytics *Data Modelling *Data Visualisation *Data Storytelling and Reporting Soft Skills *Problem Solving *Critical Thinking *Business Acumen *Communication *Curiousity *Learning Mindset #businessanalyst #businessanalytics #dataanalyst

Data Analyst Process in a Nutshell 🔍 1️⃣ Define the Problem: Understand the business question or problem you're addressing with data. 2️⃣ Data Collection: Gather relevant data from various sources like databases, spreadsheets, or APIs. 3️⃣ Data Cleaning: Remove inconsistencies, handle missing values, and ensure data quality. 4️⃣ Exploratory Data Analysis (EDA): Dive into the data, spot trends, outliers, and patterns using visualizations. #dataanalyst #datascience

As a Data Engineer do we need to understand the businesses or is it just the work of a Data Analyst? 📍Yes, Even as a Data Engineer we have to understand the business to a certain level. This is because the Data Architecture of the project is greatly influenced by the business models. If we are aware of how the business works then only we will be able to understand the data which will help us design better data models, improve the data quality and ultimately provide the best possible and optimised data solutions. Now, the context to which I have to understand the business and a data analyst has to understand the business are quite different. For instance, As a data engineer I will focus more on understanding how the business operates, functions, how the data is getting generated at various points and how the associated workflow looks like. Whereas a data analyst will dive more deep into the business to understand how the GP-PSF is being calculated, what's the logic associated with STR calculation, etc. #dataengineering #dataanalytics #data

A Data Analyst almost always has to deal with the fire of; Debugging Data, Data cleaning, Choosing the right visualizations, etc. But all what the rest of the world sees and care about are the beautiful dashboards, and the business upscaling insights. what's the greatest fire you often deal with as a Data Analyst??? #Data_Analyst #Business_Analyst #MACs_INSIGHTFUL_ANALYTICS🔎📉

A Data analyst must note these to be able to successfully result to a good end on any task given. # Collection of data(Data gathering) # Ability to clean your data(Data cleaning) # Further processing(Data processing) # Ability to manipulate(Data manipulation) # Visualize(Data visualization) # Interprete correctly(Data interpretation).

#Yes or #No? As a data analyst, I often find myself delving into the world of binary decisions—yes or no. These simple yet powerful choices can shape the strategies you develop and the insights you uncover. Why is "Yes or No" so critical in data analytics? 🟨Data Cleaning: Should you keep or discard a data point? A "yes or no" decision ensures data integrity and accuracy. 🟨Hypothesis Testing: Is there a significant difference in your data? The outcome often boils down to a "yes or no" answer, guiding your next steps. 🟨Model Selection: Should you deploy a model based on its performance metrics? A clear "yes or no" can save resources and improve efficiency. 🔸🔸🔸 Please engage in the comment section: 🟨Do you have a "yes or no" decision you're grappling with in your data projects? 🟨How do you handle binary decisions in your data analysis workflow? 🔸🔸🔸 I'm here to provide insights and solutions tailored to your data needs. 🔸🔸🔸 I'm Chidinma, your go-to for turning complex data into clear, actionable insights. Connect with me to learn more.

As a data analyst, it's important to have a combination of technical and soft skills. Some essential technical skills include querying data with SQL and Data Visualization. #dataanalysis #dataanalyst #data #skills

🔍 The Role of a Data Analyst: Unraveling" Data for Informed Decisions 🔍 Data analysts play a crucial part in helping businesses make smarter choices. From exploring data and creating visualizations to ensuring data accuracy and providing actionable recommendations, we turn data into insights that drive strategy. #DataAnalytics #DataVisualization #BusinessIntelligence #InformedDecisions