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Analytics Powerpoint Template

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Transcript: CheeseCake Factory Inventory (Beginning inventory + purchases) – Ending Inventory = Usage) -Organize Your Restaurant Inventory -Count Your Inventory -Calculate Usage -Determine Your Order Once you figure out the average usage for each item in your inventory, you can easily determine how much to order. -Importance: Potential loss of $$$ -Data: Measuring total labor hours compared to total traffic -Decide: -Overstaffed? -Understaffed? -Correctly staffed? Operation Hours -Importance: Losing money on a controllable issue. -Data: Measuring success nearing the opening and closing times -Decide: -Open later? -Close earlier? -Leave as is? Marketing Effectiveness Dishes Ordered per Table Customer Satisfaction -The Customer is Always Right -Simple After-Meal Survey -Provides Important Feedback and Demographics Wait Time -For a Table, Food, Water Glass Refill, Total Time Spent at the Restaurant, and Time of Arrival -Hire an Observer to Collect Data Nationwide. -Create a Restaurant That Is: -More Efficient -More Reflective of Customer’s Preferred Eating habits -Keep a record of how many tables have purchased alcoholic beverages based on their check. -Keep a detailed record of which alcohols are most commonly ordered as well as soft drinks -In order to improve promote specials of those most popular items -Monitor gross profit and turnover Measuring desert and appetizer orders -Keep tabs on all items ordered besides main course items -Check and see which items sell the most and to what types of people -Have a few specialty deserts and appetizers that serves can recommend while the client is ordering -Monitor waste and stock turnover Measure customer loyotality Overstaffing vs. Understaffing Bar & Cellar Management


Transcript: Data Analytics What's Data analytics? Introduction About Data analytics (DA) is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software The Science + DATA ANALYTICS INCLUDES Data Mining Predictive Analytics Applied Analytics Statistics _ More data = more storage space More storage = more money to spend  (RDBMS server needs very costly storage) Data coming faster --> Speed up data processing or we’ll have backlog Needs handle various data structure Needs to handle various data structure. How do we put JSON data format in standard RDBMS? Hey, we also have XML format from other sources. Other system give us compressed data in gzip format. CHALLENGES ANALYTICS IS IN YOUR BLOOD ANALYTICS Do you realize that you do analytics everyday? I need to go to campus faster! Hmm.. Looking at the sky today, I think it’ll be rain. ANALYTICS Atomic Ideas LifeCycle Explore all the ideas! Analytics Analytics ANALYTICS TOOLS Life Cycle 1 RapidMiner provide built-in RDBMS connector, parser for common data format (csv, xml), data manipulation, and many machine learning algorithm. We can also create our own library. Latest version of RapidMiner can connect to Hadoop and do more complex analysis like text mining. Free version is available (community edition). 2 KNIME. Known as a powerful tools to do predictive analytics. Overall function is similar to RapidMiner. Latest version of KNIME can connect to Hadoop and do more complex analysis such as text mining. Free version is available. 3 QlikView Similar to Tableau, QlikView designed to enable data analyst to develop a dashboard or just simple visualization on top of the data. Free version is available 4 Tableau is one of the famous tools to build visualization on top of the data. Tableau also powerful to create interactive dashboard. Free version is available with some limitation WorkFlow WorkFlow ?


Transcript: Twitter followers Thank you Accumulate and analyze polling and political data from hundreds of sources generated on a daily basis in a way that is informed, accurate and attractive Meet Patil Saheb writer, analyst and partner at a sports media company called Baseball Prospectus Analytics ...Velocity No of electors in the US Presidential electoral college Variable 635,803 50k insider Sam Wang Neuroscientist, Professor. Founded the Princeton Election Consortium - polling meta-analysis since 2004. Irony WHO CARES? Volume Predicted all states correctly Starting salaries LPA Variable Fill in the Blanks Percentage of states (49 out of 50) where he predicted the outcome of the US Presidential elections correctly 538 Firstly, Weighting by reliability. Secondly, regression estimate based on the demographics. Thirdly, inferential process to compute a trend. ‘current scenario’. Even where no recent elections have happened Fourthly, we simulate the election 10,000 times Velocity 4 8-14 jobs in India in next 2 years Why bother? 4 things you need to be an How will you take advantage? 1. Polling Average 2. Trend Adjustment 3. Regression 4. Snapshot: Estimate of what would happen if the election were held today. 5. Projection: What will happen in the election 6. Simulation: Simulate our results 10,000 times 6 50 Attention to detail Big Data, Big Advantage. Big Deal? Highest Rank on Amazon non fiction Repeat until numb Ifferent ers make sense O Steps Intelligence In His own words... ? ` If you smiled, this presentation is for you Compile data from everybody ELSE's surveys the ability to look at a problem in different, creative ways. Going up to LPA No guarantees, though.... Gaurav Vohra - Jigsaw 98 Nate D Data Science Amit Chatterjee - HP 4,183 Twitter Followers Volume Technical expertise Curiosity Storytelling Cleverness: 5-9 Nathaniel Silver

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