Data Analytics’ Post

Data analysis should start with a well-formulated question or research objective, rather than simply performing analysis on available data. This approach leads to more efficient, meaningful, and actionable insights that can drive informed decision-making. #data_analysis

Its been an amazing journey, Just wrapped up my data analysis certification and learned so much about data cleaning techniques and statistical analysis methods. One key takeaway: the importance of data accuracy in decision-making. Can't wait to dive deeper into this fascinating field!" #Tech4dev #WTboothcamp #DataAnalysis #CareerGrowth

Too often steps 1 and 2 are ignored in data analysis and people jump to step 3 and interpret the information. In case of qualitative data: 1.    Clarify the problem statement and purpose of the analysis 2.    Data reduction Sort and systematize by grouping similarities. simplify data by summarizing large texts. apply connections. Best method is ecosystem mapping in a hierarchical dependency – breaking down the whole into smaller parts and then showing dependencies and resource flows by connecting interconnected parts. make sure to rely on fundamentals, repetitive info from raw data and stay away from assumptions. 3.    Interpret impressions and information. Discuss results and reflect (mirror personal experiences and knowledge) on them. 4.    Document findings. Discuss possible consequences. 5.    Suggest use cases and opportunities. Data has to be processed in order to be nuanced and analysed. #increasingtimesvalue #dataanalysis

𝗠𝘆𝘁𝗵𝘀 𝘃𝘀. 𝗙𝗮𝗰𝘁𝘀 - 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 This PDF clarifies common myths and facts about data analysis. Ideal for both aspiring and experienced professionals looking to understand the realities of this dynamic field.

Unlocking insights through data analysis is key for informed decision-making. But the true power lies in validation through reviews. Reviews not only affirm accuracy but also foster continuous improvement, ensuring our analyses reflect reality. Embrace reviews as a vital step in the data analysis journey! This picture shows what you think of yourself matter thank what you look like or passing through at the moment. #DataAnalysis #ReviewsMatter #ContinuousImprovement"

Solving real-life data analytics problems requires a structured approach, a deep understanding of data and business, and the ability to translate findings into business insights. I have written an article for a step-by-step guide, from problem definition to implementing solutions, emphasising the importance of context, objectives, and stakeholder requirements. Part 2 coming soon that will focus on your thought process for any problem solving. Follow the link here for the article: https://lnkd.in/dQN4UBya

Unlock the power of data! Join our upcoming workshop to learn the latest data analysis techniques and tools. Enhance your skills, boost your career, and make data driven decisions with confidence. Register now and get ready to uncover valuable insights! #DataAnalysis #Scientificresearch #CareerGrowth #SBZbiosolutions

Good to to analyze, forecast , budget , and find gaps for improvement and easy to visualize the results.

Data analysis is an iterative process. Stay curious and continuously refine your analysis. New insights often emerge when you revisit the data with fresh eyes or a new hypothesis.

Organizations need to understand the importance of good and consistent data practices to aid in understanding its own performance and to perform environmental scanning of threats and changes that will impact business as usual.