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By implementing this approach, businesses can unlock the hidden value within unstructured data, enabling smarter decisions, identifying market opportunities, and driving innovation. The ability to harness this data effectively is becoming a key differentiator in today’s digital world.

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Step 7: Present Insights and Measure Results

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Step 7: Present Insights and Measure Results

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What to do:

Share the results in a clear and actionable format, like a report or dashboard.

Use these insights to take action, such as:

1. Improving product recommendations.

2. Launching new services based on customer needs.

3. Adjusting marketing strategies based on feedback trends.

Measure the impact by tracking:

1. Increased sales.

2. Better customer satisfaction scores.

3. Process improvements.

Why it matters: The ultimate goal is to turn insights into real results. Measuring the impact ensures that the effort spent on analysis translates into tangible business benefits.

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1. Muhammad Aizad Bin Azmi (4243003171)

2. Muhammad Nazrin Daniel Bin Rosli (4243003181)

3. Muhammad Norkhaiqal Bin Norhaidi (4223003611)

4. Darwish Khaireil Bin Mohd Fauzi (4223002231)

5. Misha A/P Manimaran (4232014022D)

6. Yuvathini A/P Kobeekrishnan (4232009051D)

7. Nur Najihah Binti Mohamad Rosdi (4241000251)

8. Mardhiah Binti Mohd Zaid (4243003081)

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Step 6: Analyze Patterns and Perform Text Mining

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Step 6: Analyze Patterns and Perform Text Mining

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What to do:

Use tools like natural language processing (NLP) to find patterns, relationships, and important information in the text.

Identify key entities like names, locations, or products.

Detect themes or trends in the data.

Analyze sentiment to understand customer opinions either it is positives or negatives one.

Why it matters: Finding patterns helps you uncover valuable insights, such as what customers like or dislike, emerging trends, or opportunities for improvement.

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What to do:

Clean and organize the data to make it ready for analysis by :

1. Remove extra spaces, symbols, and irrelevant information.

2. Eliminate duplicate entries to avoid skewed results.

Transform the data for easier use:

1. Convert all text to lowercase.

2. Break text into smaller pieces like word or phrases and focus on important ones.

Why it matters: Clean, organized data is essential for accurate analysis. Without this step, the results may be misleading or incorrect.

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Step 2: Define the Purpose of the Analysis

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Step 2: Define the Purpose of the Analysis

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What to do: Decide what you want to achieve with the analysis. Be very clear about the goals and outcomes.

For example:

﻿﻿Are you looking to identify customer trends or behavior?

﻿﻿Do you want to measure customer satisfaction or solve complaints?

﻿﻿Are you analyzing market needs for launching new products?

Why it matters: If you don't know what you're trying to achieve, the analysis won't be useful. Clear goals ensure the results are meaningful and actionable.

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Step 3: Select Technology for Data Ingestion and Storage

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Step 3: Select Technology for Data Ingestion and Storage

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What to do:

﻿﻿Choose tools that can handle large amounts of data and are suitable for your needs.

﻿﻿Consider tools or platforms that:

1. ﻿﻿﻿Work in real-time for example something for tracking competitor prices.

2. ﻿﻿﻿Handle large data volumes without losing information important for things like social media data.

3. ﻿﻿﻿Separate and secure sensitive customer data when needed multi-
tenancy.

Why it matters: Using the right technology ensures your data is managed efficiently, stored safely, and processed effectively for analysis.

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What to do:

﻿﻿Save all unstructured data in its raw form in a central location like a data warehouse or data lake.

﻿﻿Keep metadata or more likely additional details about the data for easier analysis later.

Why it matters: Storing the original data allows flexibility for different types of analysis in the future. It also ensures you don't lose any valuable information.

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What to do: Look at all the potential sources of unstructured data that are relevant to your goals. Unstructured data includes anything that isn't organized neatly, such as:

﻿﻿Social media posts

﻿﻿Emails or chat messages

﻿﻿Videos, audio files, and images

﻿﻿Customer reviews or feedback

﻿﻿Web pages or documents

Why it matters: Not all data is helpful. Focusing on the most relevant sources ensures you work efficiently and don't waste time on unnecessary data.