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This document summarizes an analysis of content on the Social Buzz platform to identify the top 5 most popular categories. It finds that Science and Technology are the most popular categories, comprising 25% and 21% of engagement from the top 5 categories. Food was identified as the third most popular category, receiving 1091 reactions in February. The summary recommends that Social Buzz could create a campaign partnering with healthy eating brands to boost engagement based on this insight into popular categories among its users. It also suggests taking this initial analysis to large-scale production for real-time understanding of trends.
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The document summarizes a project for Social Buzz, a technology company, to analyze over 36.5 million pieces of user-generated content per year to identify the top 5 most popular categories. It outlines the agenda, including recapping the project goals of assessing Social Buzz's data practices and making recommendations for its upcoming IPO. It then describes the analytics team and 5-step process for data modeling, cleaning, understanding, analysis, and uncovering insights. Key insights found the top categories were animals and science, January had the most posts, and over 16 unique categories and 1897 reactions to animal posts were identified.
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The document provides a summary of a data analysis project conducted by Accenture for Social Buzz, a technology unicorn. The project aimed to analyze over 1,00,000 daily posts to identify the top 5 most popular categories of content. The analysis found the top 5 categories to be Animals, Science, Healthy Eating, Technology, and Food. These categories accounted for 64% of total user reactions. The summary recommends Social Buzz create a campaign partnering with healthy eating brands to boost engagement, as food was identified as one of the top categories.
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Social Buzz is a fast growing technology company that needs to adapt quickly. An Accenture team has begun a 3 month project to audit Social Buzz and provide recommendations for a successful IPO. The team will analyze over 100,000 daily posts to identify the top 5 most popular content categories and uncover insights that can help Social Buzz better capitalize on the large volume of content it receives each year. The project involves data understanding, cleaning, modeling, analysis and insight generation to help Social Buzz succeed.
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Social Buzz is a fast growing tech company that processes over 100,000 posts per day. An analytics team was tasked with auditing Social Buzz's data practices, making recommendations for an upcoming IPO, and analyzing content to find the top 5 most popular categories. The analysis revealed that Animals was the most popular category, garnering 1,897 reactions. March saw the most activity overall. A total of 972 users were identified across the top 5 content categories.
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The document summarizes a project for Social Buzz, a technology company, to analyze over 36.5 million pieces of user-generated content per year to identify the top 5 most popular categories. It outlines the agenda, including recapping the project goals of assessing Social Buzz's data practices and making recommendations for its upcoming IPO. It then describes the analytics team and 5-step process for data modeling, cleaning, understanding, analysis, and uncovering insights. Key insights found the top categories were animals and science, January had the most posts, and over 16 unique categories and 1897 reactions to animal posts were identified.
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Social Buzz is a fast growing technology company that needs to adapt quickly. An Accenture team has begun a 3 month project to audit Social Buzz and provide recommendations for a successful IPO. The team will analyze over 100,000 daily posts to identify the top 5 most popular content categories and uncover insights that can help Social Buzz better capitalize on the large volume of content it receives each year. The project involves data understanding, cleaning, modeling, analysis and insight generation to help Social Buzz succeed.
Data Analytics template - Task 3_final.pptx.pptx
Social Buzz is a fast growing tech company that processes over 100,000 posts per day. An analytics team was tasked with auditing Social Buzz's data practices, making recommendations for an upcoming IPO, and analyzing content to find the top 5 most popular categories. The analysis revealed that Animals was the most popular category, garnering 1,897 reactions. March saw the most activity overall. A total of 972 users were identified across the top 5 content categories.
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4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
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Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Low power architecture of logic gates using adiabatic techniques
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
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- 2. Today's agenda Project recap Problem The Analytics team Process Insights Summary
- 3. S Project Recap Social Buzz is a fast growing technology unicorn that need to adapt quickly to it’s globle scale. Accenture has begun a 3 month POC focusing on these tasks: • An audit of Social Buzz’s big data practice • Recommendations for a successful IPO • Analysis to find Social Buzz’s top 5 most popular categories of content
- 4. Problem Over 100000 posts per day 36,500,000 pieces of content per year! But how to Capitalize on it when there is so much? Analysis to find Social Buzz’s top 5 most popular categories of content
- 5. The Analytics team ANDREW FLEMING Chief Technology Architect MARCUS ROMPTON Senior Principal GOURAV SINHA Data Analyst
- 6. Process 1 2 5 4 3 Data Understanding Data Cleaning Data Modelling Data Analysis Uncover Insights
- 7. Insights 16 Unique Categories 1091 Reactions to “Food” posts February Month with most posts
- 8. 1353 1134 1091 971 898 TECHNOLOGY SCIENCE FOOD ANIMALS HEALTHY EATING Categories Aggregate "Popularity" score Top 5 Categories by aggregate "Popularity" score
- 9. 25% 21% 20% 18% 16% POPULARITY PERCENTAGE SHARE FROM TOP 5 CATEGORIES Technology Science Food Animals Healthy Eating
- 10. Summary ANALYSIS Science and Technology are the most popular categories of content showing that people enjoy “real-life” and “factual” content the most. INSIGHT Food is a common theme with the top 5 Categories with “Science” ranking the highest. This may give an indication to the audience within your user base. You could use the insight to create a campaign and work with healthy eating brands to boots user engagement. NEXT STEPS This ad-hoc analysis is insightful, but it’s time to take this analysis into large scale production for real-time understanding of your business. We can show you how to do this.
Editor's Notes
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