Instructions for Data Analysis Services

1. Descriptive Analysis

📌 Instructions:

• Provide raw data in Excel, CSV, or database format.
• Specify key metrics and summaries required.
• Indicate any particular data visualization needs (charts, tables, etc.).

2. Predictive Analysis

📌 Instructions:

• Submit historical data with relevant variables.
• Define the outcomes you want to predict.
• Mention any preferred forecasting models (e.g., regression, AI, machine learning).

3. Prescriptive Analysis

📌 Instructions:

• Describe the problem and decision-making process.
• Provide past data and any constraints affecting decisions.
• Specify whether recommendations should be rule-based or AI-driven.

4. Diagnostic Analysis

📌 Instructions:

• Submit datasets showing past trends and anomalies.
• Specify key areas where cause-and-effect relationships need analysis.
• Include contextual information (e.g., marketing campaigns, external factors).

5. Exploratory Data Analysis (EDA)

📌 Instructions:

• Provide unstructured/raw datasets in any format.
• Indicate variables and attributes for analysis.
• Highlight specific patterns or correlations of interest.

6. Data Cleaning & Preprocessing

📌 Instructions:

• Submit raw data with any known issues (missing values, duplicates, etc.).
• Specify preferred handling of missing/incorrect values.
• Indicate whether standardization or normalization is required.

7. Business Intelligence (BI) Analysis

📌 Instructions:

• Provide access to databases or API connections.
• List key performance indicators (KPIs) to track.
• Indicate preferred dashboard tools (e.g., Power BI, Tableau, Looker).

8. Market Research & Customer Analytics

📌 Instructions:

• Submit customer demographics, transaction history, and survey data.
• Define target audience segments for analysis.
• Specify marketing objectives and key insights required.

9. Financial Data Analysis

📌 Instructions:

• Provide financial statements, transaction records, or budget reports.
• Indicate risk factors, investment strategies, or forecasting needs.
• Specify if reports should align with accounting standards (e.g., IFRS, GAAP).

10. Healthcare & Medical Data Analysis

📌 Instructions:

• Submit anonymized patient records or medical reports.
• Specify areas of focus (disease patterns, drug efficiency, patient demographics).
• Ensure compliance with data privacy laws (HIPAA, GDPR).

11. Sentiment & Text Analysis

📌 Instructions:

• Provide text-based data (customer reviews, social media comments, surveys).
• Define sentiment categories (positive, neutral, negative).
• Indicate if AI-based NLP (Natural Language Processing) should be used.

12. Big Data & Cloud Analytics

📌 Instructions:

• Share large-scale datasets or cloud storage access details.
• Define processing and storage requirements.
• Indicate whether real-time or batch processing is needed.

13. Time Series Analysis

📌 Instructions:

• Provide sequential data with timestamps (e.g., sales records, stock prices).
• Define forecasting periods (daily, weekly, monthly).
• Specify smoothing techniques (moving averages, ARIMA, etc.).

14. Geospatial Analysis

📌 Instructions:

• Submit location-based datasets (GPS, satellite, GIS data).
• Specify mapping needs (heatmaps, boundary analysis, travel patterns).
• Indicate if spatial regression or clustering techniques should be applied.

General Guidelines for All Data Analysis Services

✅ Ensure data is properly formatted before submission.
✅ Specify deadlines and expected report formats (Excel, PDF, interactive dashboards).
✅ If confidentiality is required, sign a data security agreement.
✅ For customized analysis, contact us for a consultation.