Touqir Shah’s Post

"The Hidden Superpower in Data Analytics: The Importance of Domain Knowledge" 💡 "In the world of data analytics, having technical skills is essential, but there’s one factor that can set you apart from the rest: Domain Knowledge. 🌟 Remember, 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮𝗯𝗼𝘂𝘁 𝗻𝘂𝗺𝗯𝗲𝗿𝘀; 𝗶𝘁’𝘀 𝗮𝗯𝗼𝘂𝘁 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝘀𝘁𝗼𝗿𝘆 𝗯𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀. Having domain knowledge helps you transform data into valuable business insights. 🌍🔍 Are you looking to break into a new industry? Share your thoughts on how you’re building your domain expertise! 👇 👍 Found this helpful? Give it a thumbs up and feel free to share it with your network! Let's help each other learn more about these game-changing tools. #DataAnalytics #DomainKnowledge #CareerGrowth #InterviewPrep #ContinuousLearning"

Data Analysis: A Journey in Phases Data analysis isn't a one-size-fits-all process. It's a journey with distinct phases, each crucial for extracting meaningful insights. 1 - The ask phase 2 - The prepare phase 3 - The process phase 4 - The analyze phase 5 - The share phase 6 - The act phase By understanding these phases, we can effectively navigate the data analysis journey and extract valuable insights that drive informed decision-making. #dataanalysis #datascience #analytics #businessintelligence #data #insights

🔍 The Four Types of Data Analysis Explained 🔍 Understanding data analysis is crucial in turning raw data into actionable insights! Here’s a quick overview of the four key types: Descriptive Analysis – Summarizes past data to highlight trends and patterns. 📊 Diagnostic Analysis – Digs deeper to uncover causes behind outcomes. 🔍 Predictive Analysis – Uses trends to forecast future scenarios. 📈 Prescriptive Analysis – Recommends actions based on predictions to guide decision-making. 🗺️ These types work together to turn data into a powerful decision-making tool. Which type do you use the most? 🤔 #DataAnalysis #DescriptiveAnalytics #DiagnosticAnalytics #PredictiveAnalytics #PrescriptiveAnalytics #DataScience #DataDriven #Insights #DataVisualization #BusinessIntelligence #DataJourney #TechTips

Making the right strategic decisions can make or break a business. Data analytics provides the insights needed to navigate challenges, identify opportunities, and make data-driven decisions that support long-term success. Let The Analyst Hub help your organization turn data into actionable strategies. #TheAnalystHub #TAH #StrategicDecisions #BusinessStrategy #DataDrivenGrowth #BusinessPlanning #DataInsights

📌Start Before You Start📌 Effective data analysis requires a strategic approach that starts before data collection. By defining your objectives upfront, you ensure that you gather the right data to answer the right questions. Rushing into data collection without a clear plan can lead to wasted time and resources. The collaborative process of engaging with stakeholders is the foundation of successful data analysis. It's during these discussions that you can truly understand the business needs and tailor your analysis accordingly. Remember, data analysis is an ongoing process. As new insights emerge and the business landscape evolves, your analysis should adapt to stay relevant. #data #dataanalytics #datadriven #businessintelligence #datascience.

Creating Actionable Insights from Business Data: From Raw Data to Business Strategy Data is only valuable when it leads to actionable insights. Here's my process for turning raw data into strategic business decisions: - Data Collection: Identify the most relevant datasets. - Data Cleaning: Ensure the data is accurate and complete. - Exploratory Data Analysis (EDA): Identify trends, patterns, and outliers in the data. - Contextualize the Insights: Translate findings into business terms that decision-makers understand. - Make Data-Driven Recommendations: Use the insights to inform strategies and drive impact. What’s your process for transforming data into action? #ActionableInsights #BusinessStrategy #BusinessDataAnalyst

Purpose of Data analysis

Starting with Purpose : Data Analysis It's crucial to understand the objectives and business goals before Collecting data. Collecting data without this understanding can lead to inaccurate insights and risky decisions. Always begin by asking: ✔️ What business goals are we trying to achieve? ✔️ What are the objectives of this analysis? ✔️ How does the data we collect align with these objectives and goals? #DataAnalysis #Data #Business #Goal #BusinessIntelligence #DataCollection #DataScience #Decisions #DataSkills #Growth #Success #Share

I couldn't agree more! it's not only vital to understand the business objectives before you start analysis but to also be fluid in your plan to achieve those objectives. Objectives and priorities can change and its so important to have the ability to be flexible and adapt especially in a space that is forever evolving #dataanalysis #businessobjectives #effectiveplanning