Find Interview Questions for Nelito systems ltd

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I am looking for new challenges and opportunities for growth that align more closely with my career goals.

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BRD (Business Requirements Document) outlines the high-level business needs and objectives. SRS (Software Requirements Specification) details the functional and non-functional requirements for the software. Use Case documents describe specific interactions between users and the system to achieve particular goals.

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Content analysis is a research method used to systematically analyze communication content, such as texts, speeches, or media, to identify patterns, themes, and meanings.

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To analyze data for different formats like pivot tables and matching datasets, you should:

1. **Identify Key Variables**: Determine the key fields that will be used for matching and pivoting.
2. **Clean the Data**: Ensure that the data is free from duplicates, errors, and inconsistencies.
3. **Use Pivot Tables**: Create pivot tables to summarize and analyze the data by aggregating values based on categories.
4. **Match Data**: Use functions like VLOOKUP or JOIN operations in SQL to match data from different sources based on the identified key variables.
5. **Validate Results**: Check the accuracy of the matched data and the pivot table outputs to ensure they meet business requirements.

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To depict dependency in MS Project, you can link tasks by selecting the tasks you want to connect, then clicking on the "Link Tasks" button in the toolbar or using the shortcut Ctrl + F2. This creates a finish-to-start dependency by default. You can also adjust the type of dependency (finish-to-start, start-to-start, finish-to-finish, or start-to-finish) by double-clicking on the task and modifying the "Predecessors" tab.

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In quantity surveying, 'zero value' refers to items or work that are included in a project but do not have a cost associated with them, often because they are not expected to incur any expenses or are accounted for in other ways.

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A procurement administrator is responsible for managing the purchasing process, which includes sourcing suppliers, negotiating contracts, processing purchase orders, maintaining inventory levels, and ensuring compliance with procurement policies.

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The core features of project management include:

1. **Planning**: Defining project goals, scope, and tasks.
2. **Scheduling**: Creating timelines and deadlines for project milestones.
3. **Resource Management**: Allocating and managing resources effectively.
4. **Risk Management**: Identifying and mitigating potential risks.
5. **Communication**: Facilitating clear communication among stakeholders.
6. **Monitoring and Control**: Tracking progress and making adjustments as needed.
7. **Quality Management**: Ensuring deliverables meet required standards.
8. **Documentation**: Maintaining records of project activities and decisions.

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IS 456:2000

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1 brass of sand is approximately 1,000 kilograms.

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The different types of data distributions include:

1. Normal Distribution
2. Binomial Distribution
3. Poisson Distribution
4. Uniform Distribution
5. Exponential Distribution
6. Log-Normal Distribution
7. Geometric Distribution
8. Beta Distribution
9. Chi-Squared Distribution
10. Student's t-Distribution

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Outliers are data points that significantly differ from the rest of the dataset. They can skew results and affect statistical analyses. To handle outliers, you can:

1. Identify them using methods like the IQR (Interquartile Range) or Z-scores.
2. Remove them if they are errors or irrelevant.
3. Transform them using techniques like log transformation.
4. Use robust statistical methods that are less affected by outliers.
5. Analyze them separately if they provide valuable insights.

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1. Remove duplicates
2. Handle missing values
3. Correct inconsistencies
4. Standardize formats
5. Filter out irrelevant data
6. Validate data accuracy
7. Normalize data if necessary

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A hypothesis is a specific, testable prediction about the relationship between two or more variables. To test a hypothesis, you can use the following steps:

1. **Formulate the Hypothesis**: Clearly define the null hypothesis (no effect or relationship) and the alternative hypothesis (there is an effect or relationship).
2. **Collect Data**: Gather relevant data through experiments, surveys, or observational studies.
3. **Analyze Data**: Use statistical methods to analyze the data and determine if there is enough evidence to reject the null hypothesis.
4. **Draw Conclusions**: Based on the analysis, conclude whether the hypothesis is supported or not, and report the findings.

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Classification analysis is a data analysis technique used to categorize data into predefined classes or groups. It works by using algorithms to learn from a training dataset, where the outcomes are known, and then applying this learned model to classify new, unseen data based on its features. Common algorithms include decision trees, logistic regression, and support vector machines.