Identifying the Business Need: This involves understanding the specific How will challenges faced by the organization. Are sales declining? Is customer churn increasing? Is operational efficiency lagging? Identifying the specific pain point is crucial. For example? a retail company might want to increase customer retention.
Formulating the Research Question: The business need translates into a specific? measurable? achievable? relevant? and time-bound (SMART) research question. Instead of “Improve sales?” a more focused question might be “What factors contribute to customer churn in the last quarter? and how can we mitigate them?”
Defining Success Metrics: Establishing clear metrics is essential. What are the key performance indicators (KPIs) that will demonstrate the effectiveness of the project? For the retail example? success might be measured by a reduction in churn rate by 15% within three months.
Data Collection and Preparation How will
Once the problem is defined? the next stage job function email list involves gathering and preparing the data needed to address it. Data quality is paramount.
Identifying Data Sources: This includes internal databases? external APIs? web scraping? and surveys. For instance? a retail company might use customer purchase history from its database? social media data to understand the benefits of using the data customer sentiment? and market research reports.
Data Extraction and Cleaning
Raw data is often messy? containing inconsistencies? errors? and missing values. The data needs to be cleaned? transformed? and prepared for analysis. This might involve handling missing data? removing duplicates? clear adb directory understand and standardizing formats. Data cleaning is crucial for reliable results.
Data Transformation: Data needs to be transformed into a suitable format for analysis. This might involve aggregating data? creating new features? or converting data types. For example? transforming customer demographics into categorical variables for analysis.