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Software Requirements Specification for QAT For Business Analyst Based On Facebook & Youtube (BQAT) Version 1.0 approved Prepared by Yumna Rehman Ned University of Engineering and Technology 23 November 2019 Table of Contents Table of Contents','ii Revision History','ii 1.','Introduction','1 1.1','Purpose','1 1.2','Document Conventions','1 1.3','Intended Audience and Reading Suggestions','1 1.4','Product Scope','1 2.','Overall Description','2 2.1','Product Perspective','2 2.2','Product Functions','2 2.3','User Classes and Characteristics','2 2.4','Operating Environment','2 2.5','Design and Implementation Constraints','3 2.6','User Documentation','3 2.7','Assumptions and Dependencies','3 3.','External Interface Requirements','3 3.1','User Interfaces','3 3.2','Hardware Interfaces','3 3.3','Software Interfaces','3 3.4','Communications Interfaces','4 4.','System Features','4 4.1','Extracting Data','4 4.2','Analysing Data','4 4.3','Displaying Results','5 5.','Other Nonfunctional Requirements','5 5.1','Performance Requirements','4 5.2','Safety Requirements','5 5.3','Security Requirements','5 5.4','Software Quality Attributes','6 5.5','Business Rules','6 6.','Other Requirements','6 Appendix A: Glossary','6 Appendix C: To Be Determined List','6 No revisions yet. Revision History Name Date Reason For Changes Version             Introduction Purpose The purpose of this document is to present a detailed description of Qualitative Analysis Tool for Business Anlysis Based in Facebook and Youtube. This document enlists the features and constraints under which it must operate. The document is intended for software users, project team and external and internal auditors. Document Conventions The document is prepared by following IEEE standard for System Requirement Specification Document. Intended Audience and Reading Suggestions The document is intended for; Project team so they can follow the requirements while development and articulate any changes made during the project lifecycle into the document. Teachers and external and internal auditors so they can understand the project and evaluate our project based on these specifications. Users that want to use the tool. Product Scope The emergence in the last decade of social media platforms such as Twitter, Facebook, and Instagram, enabled people to engage in social activities to express their opinions, thoughts, and emotions on a variety of topics. On such platforms, large amounts of data are produced (e.g.: Facebook generates 4 new petabytes of data per day), this representing an opportunity for companies to assess their social influence and people opinions towards their products. While collecting data has never been easier, the bigger challenge is bringing it all together in a meaningful way. With data spread across so many different formats, finding connections can be extremely difficult and time consuming without the right tools. Consequently, a computational framework is desirable to perform opinion mining which can adapt to the activity domain of the user. Qualitative Analysis of data of various individual platform is highly costly so we provide a cost-effective tool which takes the dataset of multiple platforms and analyze that data. Brands use it to find and measure customer opinions and attitudes towards their products, services, campaigns. Our tool helps them to analyze data of social media that will provide digital consumer insights and can determine brand reputation, improve customer experience, stop issues becoming a crisis, determine future marketing strategies, improve marketing campaigns and product messaging, identify brand influences, test business KPIs and generate leads. Overall Description Product Perspective Our project is the automated process that uses machine learning for identifying subjective information from text. Companies use qualitative analyzing of data such as tweets, survey responses and product reviews, getting key insights and making data-driven decisions. It is about the contextual mining of text which identifies and extracts subjective information in source material, and helping a business to understand the reviews of their brand, product or service while monitoring online conversations. However, analysis of social media streams is usually restricted to just basic sentiment analysis and count based metrics. This is akin to just scratching the surface and missing out on those high value insights that are waiting to be discovered. For a market researcher, collecting qualitative data helps in answering questions like, who their customers are, what issues or problems they are facing and where do they need to focus their attention so problems or issues are resolved. For qualitative analyzing of data of social media, videos and documents, we use the algorithms like Correlation Analysis, Regression Analysis, and Descriptive statistics (Mean, Median, Mode, Geometric Mean and Standard Deviation) for analyzing the data and represent it statistically which is really helpful foot the upper management of any business to take decision. Product Functions Business Analyst can analyse their data by inserting their Channel ID in the platform. Analyse the data by processing the algorithm. Choose the graph to view the data statistics. Get the result graphically. They can go to Support option to get guidelines. User Classes and Characteristics Our targeted users are all the Business Analyst around the world they may include; The Business Analyst that want to gain insights of his customer. Marketing Specialist that want to know about marketing parameters and user’s interest and priorities. Product Manager that wanted to know all about his product. Business Consultant that quickly analyse the different products and to watch trends and bring high value by implementing industry best practices to reach the goals of a particular project. Operating Environment BQAT is a web based tool for qualitative analysis of data of Facebook and Youtube. So it can be accessible by browser through internet. Design and Implementation Constraints Design constraint: The tool uses the Youtube Data API. It is being developed on Windows platform using php, Javascript, Bootstrap, python(for algorithm processing) and mysql databses on any editor and Python IDE. Time constraint: The project is estimated to be completed by mid-June 2020. Resource constraint: There is a limitation in testing the tool on multiple products. Facebook data extraction requires the admin rights to extract the data and every brands is not entertaining us. When we doing testing we must have admin rights of atleast two or three pages brand products and we are looking for it. User Documentation The tool’s user interface contains a support option that will provide guidelines and documentations. The separate user documentation is not prepared yet. Assumptions and Dependencies Assumptions: We assume that the user that want to analyse his data must have meaningful business products. Dependencies: The tool depends on the Data which is extracted through API and user can must provide his channel ID or have to provide secret key for facebook page’s data., that means that he tool heavily depends on external APIs in order to operate as intended. External Interface Requirements User Interfaces UI designing is still in process so screens can’t be documented here. Hardware Interfaces Theminimal hardware that will be required for the development of BQAT is a PC of good configuration for webserver and internet. Software Interfaces The tool interacts with Youtube Data API and Facebook Graph API for data retrieval. Data items going into the databases: ‘Go for Analysis’ a message sent as a request to analyse the data . Comments, like, dislikes, description which are extracted from Facebook or Youtube make the themes upon user requst. Result shows: Graphical representation of themes returned from the system after performing the analysis. The insights and data is represent statistically or graphically. Communications Interfaces The tool requires the PC to be connected on internet for operation. The requests and responses directly depend on APIs so every request made by user should use internet. System Features This section demonstrates the tool’s most prominent features, how they work and what input they requires to produce expected outputs. Extracting Data: Description and Priority User can must have the access right of his product to retrieve the data form Youtube and Facebook. This feature has high priority because once the data is retrieve successfully every brand can easily use it and algorithm processing is also depend on the data also it is the main improvement in traditional manual analysing tools. Stimulus/Response Sequences The analysis screens will be added after UI designing is completed. Functional Requirements REQ-1: User device must be connected on internet. REQ-2: Get API key feature must be able to extract correct textual information from the Youtube Channel or from the facebook page that contain some meaningful data. 4.2: Analysing Data: 4.2.1: Description and Priority: The tool will make the theme if the extracted data efficiently by using some data dictionary resouces or may use Google Synonym API. The priority is high for this feature as it is a necessary for algoruthm processing. 4.2.2: Stimulus/Response Sequences: The screens will be added after UI designing. 4.2.3: Functional Requirements: REQ-1: Themes should be displayed in a user-friendly format. REQ-2: The theme representation must be up to date that is any changes in the source must be reflected in here. 4.3: Displaying Result: 4.3.1: Description and Priority: By analysing the themes, the display result feature will allow to sh
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Q1:- Is man clever than mrs. Oakentubb? Yes, the man clever than Mrs. Oakentubb. Explanation: Mrs. Oakentubb was clever lady. She had killed two innocent lives by fast for a bet and she lied in the court to get punishment. Hence, was clever enough to hide the real facts of the accident. She even hides label attach to her suitcase in order to hide her identity. But, the man was cleverer than Mrs. Oakentubb as though she hide her label, the man came to know about her identity and punished her for her bad deeds. Q2:- Justify the action of man? Essay:- Impact of IT
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Parallel processing can help improve performance in situations where large amounts of data need to be examined or processed, such as scanning large tables, joining large tables, creating large indexes, and scanning partitioned indexes. In order to realize the benefits of parallel processing, your database environment should not already be running at, or near, capacity. Parallel processing requires more processing, memory, and I/O resources than serial processing. Before implementing parallel processing, you may need to add hardware resources. Let’s forge ahead by looking at the components involved in parallel processing. Parallel processing can help to enhance performance in situations where big amounts of data need to be examined or processed, such as scanning large tables, joining big tables, creating large indexes, and scanning partitioned indexes. In order to realize the benefits of parallel processing, your database environment should not already be running at, or near, capacity. Parallel processing need more processing, memory, and I/O resources than serial processing. Before implementing parallel processing, you may need to add hardware resources. Let’s forge ahead by looking at the components involved in parallel processing.
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