What are the most effective ways to answer questions about your experience with data analysis?

1. Know your data sources. Know your data, where it comes from, what’s in it, what it means. It all starts from there. There are many layers Data Layout, Individual entries, Business Exceptions, Generation and collections and collection decisions.

1. know your data source : Yes , You know about the type of your study and research hypothesis. Then for knowing the flow of your work best way to design a conceptual frame of your study which gives pictorial representation of your dependent and independent variable . The data in form of questionairre either adopted or adapted by reference paper should be validated and reliability analysis has to be done before collection of data whether the instruments or constructs use in your questionairre are reliable and can be a true representation of your data or not . It makes easy for you to justify your problem statement

Your portfolio in research can be sketch by how you analyze your data . what statistical analysis tools you use like SPSS , Stata, Excel, Hayes process, Process Capability , Tabeleau and also present your data by using dashboards of PowerBI and Excel advance tools. Your data interpretation of results you have by analysis can autheticate your data source

As per analysis the interpretation plays a pivitol role in sketching your data results in publishing any esteemed and recognized journal. Your interpretation increases citation and impact of your research work . Dashboards now adays easy to showcase your skills in data analysis field

Your ethical values is always be a challenge in the journey of data analyst. You have to accept your gaps avoid biasness and manipulation in your data. Sometimes your insignificant data get your target audience due to your fairness over significant manmade manipulated data. You have to address your limitation for forth-coming researchers for betterment of community by providing quality research work.

Continous improvement and learning is the mantra for a success in data analyst life. You have to polish your skills as a daily chore. Like even in excel you have to explore everyday you know about new features of excel. From my experience after working in research field for almost 5 years. I currently, know how to analyze data in excel, power BI , process capability, PLS modelling, SPSS. when you learn its a magical world to explore. Coursera, youtube tutorial, linkedin learning platforms for beginners to advance level. Keep going ultimately you grow.

The issues with most of the data and information professionals are that: 1. They don’t look at the entire lifecycle holistically and usually forget to factor in the daily technical maintenance and administration overheads. 2. They don’t review or have proper access, permissions, retention and destruction processes/procedures. 3. Security and restoration is the last items being overlooked from business continuity and recovery perspectives.