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Let’s analyze the Python code snippet from the image:

python
Copy
Edit
def add_n(a, b):
    return (a + b)

a = 5
b = 5

print(add_n(4, 3))
Step-by-step explanation:
A function add_n(a, b) is defined to return the sum of a and b.

The variables a = 5 and b = 5 are declared but not used inside the function call — they are irrelevant in this context.

The function is called with explicit arguments: add_n(4, 3), so:

python
Copy
Edit
return 4 + 3  # = 7

✅ Correct answer: C. 7

𝟰 𝗠𝘂𝘀𝘁-𝗪𝗮𝘁𝗰𝗵 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗘𝘃𝗲𝗿𝘆 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗦𝘁𝘂𝗱𝗲𝗻𝘁 𝗶𝗻 𝟮𝟬𝟮𝟱😍

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Data Analyst vs Data Engineer: Must-Know Differences

Data Analyst:
- Role: Focuses on analyzing, interpreting, and visualizing data to extract insights that inform business decisions.
- Best For: Those who enjoy working directly with data to find patterns, trends, and actionable insights.
- Key Responsibilities:
- Collecting, cleaning, and organizing data.
- Using tools like Excel, Power BI, Tableau, and SQL to analyze data.
- Creating reports and dashboards to communicate insights to stakeholders.
- Collaborating with business teams to provide data-driven recommendations.
- Skills Required:
- Strong analytical skills and proficiency with data visualization tools.
- Expertise in SQL, Excel, and reporting tools.
- Familiarity with statistical analysis and business intelligence.
- Outcome: Data analysts focus on making sense of data to guide decision-making processes in business, marketing, finance, etc.

Data Engineer:
- Role: Focuses on designing, building, and maintaining the infrastructure that allows data to be stored, processed, and analyzed efficiently.
- Best For: Those who enjoy working with the technical aspects of data management and creating the architecture that supports large-scale data analysis.
- Key Responsibilities:
- Building and managing databases, data warehouses, and data pipelines.
- Developing and maintaining ETL (Extract, Transform, Load) processes to move data between systems.
- Ensuring data quality, accessibility, and security.
- Working with big data technologies like Hadoop, Spark, and cloud platforms (AWS, Azure, Google Cloud).
- Skills Required:
- Proficiency in programming languages like Python, Java, or Scala.
- Expertise in database management and big data tools.
- Strong understanding of data architecture and cloud technologies.
- Outcome: Data engineers focus on creating the infrastructure and pipelines that allow data to flow efficiently into systems where it can be analyzed by data analysts or data scientists.

Data analysts work with the data to extract insights and help make data-driven decisions, while data engineers build the systems and infrastructure that allow data to be stored, processed, and analyzed. Data analysts focus more on business outcomes, while data engineers are more involved with the technical foundation that supports data analysis.

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Hope it helps :)

𝟲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗙𝗿𝗼𝗺 𝗧𝗼𝗽 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 😍

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