{"payload":{"feedbackUrl":"https://github.com/orgs/community/discussions/53140","repo":{"id":627655798,"defaultBranch":"main","name":"DataAnalytics","ownerLogin":"meaganwindler","currentUserCanPush":false,"isFork":false,"isEmpty":false,"createdAt":"2023-04-13T23:30:20.000Z","ownerAvatar":"https://avatars.githubusercontent.com/u/130713287?v=4","public":true,"private":false,"isOrgOwned":false},"refInfo":{"name":"","listCacheKey":"v0:1711049164.0","currentOid":""},"activityList":{"items":[{"before":"88da3a0d61df17ea869634f60f91ffb965e0ba2d","after":"354e0ecc2188b33070efa37da088826a18b5514b","ref":"refs/heads/main","pushedAt":"2024-03-21T19:31:35.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Create SQL Create Tables Data Engineering Training Plan Example","shortMessageHtmlLink":"Create SQL Create Tables Data Engineering Training Plan Example"}},{"before":"6b9dcdebee4b610c390dc81bb67838af5d79a814","after":"88da3a0d61df17ea869634f60f91ffb965e0ba2d","ref":"refs/heads/main","pushedAt":"2024-03-21T19:26:03.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis is an ERD representing the schema for my data engineer training progress, detailing the relationships between dates, training modules, exams, skills, certifications, and training progress for data engineering.","shortMessageHtmlLink":"Add files via upload"}},{"before":"61b54afa190456cc2d4d4e5bac5fa174c113ea0b","after":"6b9dcdebee4b610c390dc81bb67838af5d79a814","ref":"refs/heads/main","pushedAt":"2024-03-21T18:47:26.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"SQL Case Statements Example","shortMessageHtmlLink":"SQL Case Statements Example"}},{"before":"581c0531022f0cef4bb38c74edb422633c5f74fe","after":"61b54afa190456cc2d4d4e5bac5fa174c113ea0b","ref":"refs/heads/main","pushedAt":"2024-03-21T18:46:19.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Delete SQL Case Statements Learning Progress Example","shortMessageHtmlLink":"Delete SQL Case Statements Learning Progress Example"}},{"before":"a831d14d3bad49ceb565fbbffdedf7254d4c5675","after":"581c0531022f0cef4bb38c74edb422633c5f74fe","ref":"refs/heads/main","pushedAt":"2024-03-21T18:40:40.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update README.md","shortMessageHtmlLink":"Update README.md"}},{"before":"1c0d1e101de50221dd780f82b7cd5272843b4666","after":"a831d14d3bad49ceb565fbbffdedf7254d4c5675","ref":"refs/heads/main","pushedAt":"2024-03-21T18:39:11.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update SQL Query Tables Business Objective Scenarios.txt","shortMessageHtmlLink":"Update SQL Query Tables Business Objective Scenarios.txt"}},{"before":"8f17b76704a2a1d511f9e2218af2f03d730fabf6","after":"1c0d1e101de50221dd780f82b7cd5272843b4666","ref":"refs/heads/main","pushedAt":"2024-03-21T18:31:44.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update SQL Joining Tables.sql","shortMessageHtmlLink":"Update SQL Joining Tables.sql"}},{"before":"c502f37def548be5a922b2c4a1b3b0657f07893e","after":"8f17b76704a2a1d511f9e2218af2f03d730fabf6","ref":"refs/heads/main","pushedAt":"2024-03-21T18:29:00.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update SQL Create and Populate Tables.sql","shortMessageHtmlLink":"Update SQL Create and Populate Tables.sql"}},{"before":"2cf9c743f5d649db6dc59c538f2472290f18d0ab","after":"c502f37def548be5a922b2c4a1b3b0657f07893e","ref":"refs/heads/main","pushedAt":"2024-03-21T18:27:03.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update and rename SQL Common Table Expressions Example.sql to SQL Case Statements Learning Progress Example","shortMessageHtmlLink":"Update and rename SQL Common Table Expressions Example.sql to SQL Cas…"}},{"before":"635e2d42f5b0629ee6e37868b258d0904e2cf2a9","after":"2cf9c743f5d649db6dc59c538f2472290f18d0ab","ref":"refs/heads/main","pushedAt":"2024-03-03T13:31:50.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nSample python code I use to automate zipping files within a folder.","shortMessageHtmlLink":"Add files via upload"}},{"before":"fae66c12a2a3ed040f2f6a87907ccf3184951361","after":"635e2d42f5b0629ee6e37868b258d0904e2cf2a9","ref":"refs/heads/main","pushedAt":"2024-03-03T13:29:59.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nSample project in Python that performs a sentiment analysis project using a Google API.","shortMessageHtmlLink":"Add files via upload"}},{"before":"67ce750b2e3efff9ac4dd1820babf7008eac1c02","after":"fae66c12a2a3ed040f2f6a87907ccf3184951361","ref":"refs/heads/main","pushedAt":"2024-03-03T13:27:52.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nSample code showing my data preprocessing in identifying outliers in a dataset utilizing Python code","shortMessageHtmlLink":"Add files via upload"}},{"before":"e8b181d11bb91f98ee829ee8f1822f54fc716752","after":"67ce750b2e3efff9ac4dd1820babf7008eac1c02","ref":"refs/heads/main","pushedAt":"2024-03-03T13:20:24.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update README.md","shortMessageHtmlLink":"Update README.md"}},{"before":"977c32ebdf0de1dee2bd326c0c49614286d478ee","after":"e8b181d11bb91f98ee829ee8f1822f54fc716752","ref":"refs/heads/main","pushedAt":"2024-03-03T13:17:58.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update README.md","shortMessageHtmlLink":"Update README.md"}},{"before":"a2dd01e12be5b443f06d6b785c208c751c787f66","after":"977c32ebdf0de1dee2bd326c0c49614286d478ee","ref":"refs/heads/main","pushedAt":"2024-03-03T13:01:40.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis SQL code showcases my proficiency in using advanced SQL features like Common Table Expressions (CTEs), conditional logic, and data aggregation to efficiently analyze and report on pharmacy claims data.","shortMessageHtmlLink":"Add files via upload"}},{"before":"1fa6d9442d0789f30e80a2283d7f559664356d97","after":"a2dd01e12be5b443f06d6b785c208c751c787f66","ref":"refs/heads/main","pushedAt":"2024-03-03T12:50:01.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nIn this project, SAS Visual Analytics and SAS Model Studio within SAS Viya were utilized to build and enhance a neural network aimed at predicting employee job satisfaction. The goal was to improve the model's precision, specifically by reducing the Average Squared Error (ASE). This improvement was critical for an HR consultancy looking to predict job satisfaction across a global employee dataset.","shortMessageHtmlLink":"Add files via upload"}},{"before":"874fab8dfebe73897d68939be89b2564c20dc506","after":"1fa6d9442d0789f30e80a2283d7f559664356d97","ref":"refs/heads/main","pushedAt":"2024-03-03T12:46:41.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nSample project to show my ability to export a proc report in Excel from SAS Enterprise","shortMessageHtmlLink":"Add files via upload"}},{"before":"569706a8f53e795744ca1a52c758da89f437d97c","after":"874fab8dfebe73897d68939be89b2564c20dc506","ref":"refs/heads/main","pushedAt":"2024-03-03T12:43:57.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nSample chart chaselist creation project for our medical providers, which demonstrates my ability to perform ad hoc analyses in SAS Enterprise 9.4.","shortMessageHtmlLink":"Add files via upload"}},{"before":"dc131921691d4a77b9897fdb040abb2f6bdf84ea","after":"569706a8f53e795744ca1a52c758da89f437d97c","ref":"refs/heads/main","pushedAt":"2024-03-03T12:40:53.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nExample of base SAS programming in SAS Enterprise 9.4 showing my ability to create macros and formats.","shortMessageHtmlLink":"Add files via upload"}},{"before":"b40e2e871b3e5bb4e71f303f2f0c6d147b9acc14","after":"dc131921691d4a77b9897fdb040abb2f6bdf84ea","ref":"refs/heads/main","pushedAt":"2024-03-03T12:37:21.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Delete Format and Macro Examples SAS9_Sanitized.sas","shortMessageHtmlLink":"Delete Format and Macro Examples SAS9_Sanitized.sas"}},{"before":"e047184a6b6b2e1f906a85f94cd50a6627f1a463","after":"b40e2e871b3e5bb4e71f303f2f0c6d147b9acc14","ref":"refs/heads/main","pushedAt":"2024-03-03T12:37:01.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Delete Format and Macro Examples SAS9_Sanitized Code.docx","shortMessageHtmlLink":"Delete Format and Macro Examples SAS9_Sanitized Code.docx"}},{"before":"f794bc158316712e19acef924975ff37e30df95b","after":"e047184a6b6b2e1f906a85f94cd50a6627f1a463","ref":"refs/heads/main","pushedAt":"2024-03-03T12:36:00.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nExample code file in SAS Enterprise 9.4 showing ability to code macros and formats","shortMessageHtmlLink":"Add files via upload"}},{"before":"9237f7a031702aedc002d81aa7d22d398a84cec3","after":"f794bc158316712e19acef924975ff37e30df95b","ref":"refs/heads/main","pushedAt":"2023-05-18T17:19:25.726Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis file contains a sample user story for a learning management system in the discovery phase.","shortMessageHtmlLink":"Add files via upload"}},{"before":"d0598670770d4b0f0a88d6da78bc35654049f407","after":"9237f7a031702aedc002d81aa7d22d398a84cec3","ref":"refs/heads/main","pushedAt":"2023-05-18T16:09:33.395Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis is an example of a cross-functional process flow created in Microsoft Visio.","shortMessageHtmlLink":"Add files via upload"}},{"before":"a21ddd2327c1751b2eeb04c3a4ef6ca1bb088c0c","after":"d0598670770d4b0f0a88d6da78bc35654049f407","ref":"refs/heads/main","pushedAt":"2023-05-18T16:01:52.924Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis document contains a sample user story to enhance the existing learning management system (LMS) by integrating the Absorb Analyze data add-on, enabling the learning systems administrator to provide precise data and insights to the HR department, sales and operations managers, and the data team, resulting in streamlined onboarding, improved compliance tracking, enhanced performance management, targeted training interventions, and improved operational efficiency.","shortMessageHtmlLink":"Add files via upload"}},{"before":"123e609257cadab2fa09524fcd2ddb515e309073","after":"a21ddd2327c1751b2eeb04c3a4ef6ca1bb088c0c","ref":"refs/heads/main","pushedAt":"2023-05-18T15:40:49.829Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Delete Sample User Story.docx","shortMessageHtmlLink":"Delete Sample User Story.docx"}},{"before":"3ce622ac002adddabadf7ccd9cb22764ac9f3111","after":"123e609257cadab2fa09524fcd2ddb515e309073","ref":"refs/heads/main","pushedAt":"2023-05-18T15:36:35.518Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThis is a sample user story to enhance the existing learning management system (LMS) by integrating the Absorb Analyze data add-on, enabling the learning systems administrator to provide precise data and insights to the HR department, sales and operations managers, and the data team, resulting in streamlined onboarding, improved compliance tracking, enhanced performance management, targeted training interventions, and improved operational efficiency.","shortMessageHtmlLink":"Add files via upload"}},{"before":"2ee3bbaafe234ed01c8f88469dd391a727e235d4","after":"3ce622ac002adddabadf7ccd9cb22764ac9f3111","ref":"refs/heads/main","pushedAt":"2023-04-28T19:09:57.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update README.md","shortMessageHtmlLink":"Update README.md"}},{"before":"f6374ddbbe2899b6938ffd2ce5282c043e730640","after":"2ee3bbaafe234ed01c8f88469dd391a727e235d4","ref":"refs/heads/main","pushedAt":"2023-04-28T19:09:34.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Update README.md","shortMessageHtmlLink":"Update README.md"}},{"before":"644067be0716c9e893e3bf031b273315b334390a","after":"f6374ddbbe2899b6938ffd2ce5282c043e730640","ref":"refs/heads/main","pushedAt":"2023-04-28T19:08:19.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"meaganwindler","name":null,"path":"/meaganwindler","primaryAvatarUrl":"https://avatars.githubusercontent.com/u/130713287?s=80&v=4"},"commit":{"message":"Add files via upload\n\nThe enclosed report explores a recent data mining project I conducted within the KNIME platform. The project was designed to use four different prediction models (two number-based and two set-based) to discover the determinants of the customer churning, which is the percentage of customers who stop using the company during a particular timeframe.","shortMessageHtmlLink":"Add files via upload"}}],"hasNextPage":true,"hasPreviousPage":false,"activityType":"all","actor":null,"timePeriod":"all","sort":"DESC","perPage":30,"cursor":"djE6ks8AAAAEHBqQ9gA","startCursor":null,"endCursor":null}},"title":"Activity · meaganwindler/DataAnalytics"}