الصفحة الرئيسية الكويت Software Engineer - Stores
الصفحة الرئيسية الكويت Software Engineer - Stores
Software Engineer - Stores
دوام كامل
في Canonical
في
Kuwait
نُشرت يوم December 8, 2024
تفاصيل الوظيفة
Summary This is an exciting opportunity for an exceptional software engineer passionate about open source software, Linux, and Web Services at scale. Come build a rewarding, meaningful career working with the best and brightest people in technology at Canonical, a growing international software company. Canonical's Store team develops and operates a large system of backend services that power the Snap Store and Charmhub.io marketplaces. Our services are built primarily in Python, with a bit of Golang. We have some exciting challenges ahead including continuing to scale our production architecture, significantly expanding the range of software we can deliver through the system powering our marketplaces, and enhancing our offering for the booming world of IoT and for large Enterprise solutions. If you have a passion for clean APIs, have a bias towards shipping, and believe that automated tests are the key to higher velocity and reliability, you'll fit right in.
What you'll do
- Collaborate remotely with a globally distributed team.
- Write clean web service APIs to support both CLI and web frontend clients, using Python (and optionally Golang).
- Design and implement new features and enhancements from spec to production and ongoing operations at scale.
- Review code and technical designs produced by other engineers.
- Discuss ideas and collaborate on finding good solutions.
- Work remotely with global travel for 2 to 4 weeks for internal and external events.
Who you are
- You have demonstrated professional proficiency in developing public-facing APIs and web applications using Python.
- You have a broad technology base but favour backend code and infrastructure.
- You know your way around relational and non-relational databases and can effectively design data models that perform well, and tune queries to access them.
- You are comfortable with Ubuntu as a development and deployment platform.
- You have demonstrated strong academic performance in Computer Science, STEM or a similar degree.
- You love technology and working with a diverse set of talented people.
- You are curious, flexible, articulate, and accountable.
- You value soft skills and are passionate, enterprising, thoughtful, and self-motivated.
About Canonical
Canonical is a growing, international software company that works with the open-source community to deliver Ubuntu -- the world's #1 cloud operating system. Our mission is to realise the potential of free software in the lives of individuals and organisations. Our services are helping businesses worldwide to reduce costs, improve efficiency and enhance security with Ubuntu. Canonical is a unique tech company - global, remote-first, open source, with 700 professionals across 50 countries - we want to be the world's best, not biggest, global software company. With almost every team remote by default, Canonical sets the pace on the 21st-century digital workplace.What Canonical offers:
- Work from home
- Learning and development allowances
- Competitive salary
- Annual compensation review
- Recognition rewards
- Generous annual leave
- Paid maternity, paternity and sick leave
- Priority Pass for travel
- Exposure to international business and technology
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'global_location_id' => '225', 'rel_gloc_ids' => '251,250,249,248,247,246,245,244,225', 'currency' => 'AED', 'currency_name' => 'UAE Dirham', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Dubai', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'saudi' => array( 'name' => 'Saudi Arabia', 'country_id' => '183', 'country_code' => 'sa', 'slug' => 'saudi', 'global_location_id' => '187', 'rel_gloc_ids' => '274,273,272,271,269,268,267,266,265,264,263,262,261,260,259,258,257,256,255,254,253,187', 'currency' => 'SAR', 'currency_name' => 'Saudi Riyal', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Riyadh', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'india' => array( 'name' => 'India', 'country_id' => '99', 'country_code' => 'in', 'slug' => 'india', 'global_location_id' => '100', 'rel_gloc_ids' => '100,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,976,994,1263,1264', 'currency' 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'job_location' => '1', 'published' => '1', 'show' => '1' ), 'singapore' => array( 'name' => 'Singapore', 'country_id' => '188', 'country_code' => 'sg', 'slug' => 'singapore', 'global_location_id' => '192', 'rel_gloc_ids' => '192,382,432,438,445,453', 'currency' => 'SGD', 'currency_name' => 'Singapore Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Singapore', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'qatar' => array( 'name' => 'Qatar', 'country_id' => '178', 'country_code' => 'qa', 'slug' => 'qatar', 'global_location_id' => '176', 'rel_gloc_ids' => '176,252', 'currency' => 'QAR', 'currency_name' => 'Qatar Rial', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Qatar', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'pakistan' => array( 'name' => 'Pakistan', 'country_id' => '169', 'country_code' => 'pk', 'slug' => 'pakistan', 'global_location_id' => '164', 'rel_gloc_ids' => 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'default_language' => 'en', 'country_time_zone' => 'Asia/Muscat', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'jordan' => array( 'name' => 'Jordan', 'country_id' => '106', 'country_code' => 'jo', 'slug' => 'jordan', 'global_location_id' => '110', 'rel_gloc_ids' => '110,958,959,1101,1247,1246,1245,1244,1243,1242,1241,1240,1239', 'currency' => 'JOD', 'currency_name' => 'Jordanian Dinar', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Amman', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'philippines' => array( 'name' => 'Philippines', 'country_id' => '168', 'country_code' => 'ph', 'slug' => 'philippines', 'global_location_id' => '171', 'rel_gloc_ids' => '171,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,1262', 'currency' => 'PHP', 'currency_name' => 'Philippine Peso', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Manila', 'job_location' => '1', 'published' => '1', 'show' => 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'226', 'rel_gloc_ids' => '226,1035,1036,1037,1038,1039,1040,1041,1042,1043,1044,1045,1046,1050,1259,1260,1261,1267', 'currency' => 'GBP', 'currency_name' => 'British Pound', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/London', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'malaysia' => array( 'name' => 'Malaysia', 'country_id' => '149', 'country_code' => 'my', 'slug' => 'malaysia', 'global_location_id' => '131', 'rel_gloc_ids' => '131,131,980,1051', 'currency' => 'MYR', 'currency_name' => 'Ringgit', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Kuala_Lumpur', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'nepal' => array( 'name' => 'Nepal', 'country_id' => '159', 'country_code' => 'np', 'slug' => 'nepal', 'global_location_id' => '151', 'rel_gloc_ids' => '151,981,1096,1097,1098', 'currency' => 'NPR', 'currency_name' => 'Nepalese Rupee', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Kathmandu', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'nigeria' => array( 'name' => 'Nigeria', 'country_id' => '155', 'country_code' => 'ng', 'slug' => 'nigeria', 'global_location_id' => '158', 'rel_gloc_ids' => '158,995,996,997,1095', 'currency' => 'NGN', 'currency_name' => 'Nigerian Naira', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Africa/Lagos ', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'newzealand' => array( 'name' => 'New Zealand', 'country_id' => '162', 'country_code' => 'nz', 'slug' => 'newzealand', 'global_location_id' => '155', 'rel_gloc_ids' => '155,998,999,1080,1081,1082,1083', 'currency' => 'NZD', 'currency_name' => 'New Zealand Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Pacific/Auckland', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'brasil' => array( 'name' => 'Brasil', 'country_id' => '29', 'country_code' => 'br', 'slug' => 'brasil', 'global_location_id' => '30', 'rel_gloc_ids' => '30,1000,1001,1002,1003,1004,1005,1006,1007,1008,1009,1010,1011,1012,1013', 'currency' => 'BRL', 'currency_name' => 'Brazilian Real', 'languages' => 'pt', 'default_language' => 'pt', 'country_time_zone' => 'America/Sao_Paulo', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'portugal' => array( 'name' => 'Portugal', 'country_id' => '175', 'country_code' => 'pt', 'slug' => 'portugal', 'global_location_id' => '174', 'rel_gloc_ids' => '174,1014,1015,1087,1088,1089,1090', 'currency' => 'EUR', 'currency_name' => 'Euro', 'languages' => 'pt', 'default_language' => 'pt', 'country_time_zone' => 'Europe/Lisbon', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'canada' => array( 'name' => 'Canada', 'country_id' => '36', 'country_code' => 'ca', 'slug' => 'canada', 'global_location_id' => '38', 'rel_gloc_ids' => '38,1019,1020,1021,1022,1023,1024,1025', 'currency' => 'CAD', 'currency_name' => 'Canadian Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Canada/Saskatchewan', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'united-states' => array( 'name' => 'United States', 'country_id' => '221', 'country_code' => 'us', 'slug' => 'united-states', 'global_location_id' => '227', 'rel_gloc_ids' => '227,1314,1315,1316,1317,1318,1319,1320,1321,1322,1323,1324,1325,1326', 'currency' => 'USD', 'currency_name' => 'US Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'America/New_York', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'angola' => array( 'name' => 'Angola', 'country_id' => '9', 'country_code' => 'ao', 'slug' => 'angola', 'global_location_id' => '6', 'rel_gloc_ids' => '6,1016,1091,1092,1093,1094', 'currency' => 'AOA', 'currency_name' => 'Angolan Kwanza', 'languages' => 'pt', 'default_language' => 'pt', 'country_time_zone' => 'Africa/Luanda', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'australia' => array( 'name' => 'Australia', 'country_id' => '14', 'country_code' => 'au', 'slug' => 'australia', 'global_location_id' => '13', 'rel_gloc_ids' => '13,1026,1027,1028,1029,1030', 'currency' => 'AUD', 'currency_name' => 'Australian Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Australia/Melbourne', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'kenya' => array( 'name' => 'Kenya', 'country_id' => '108', 'country_code' => 'ke', 'slug' => 'kenya', 'global_location_id' => '112', 'rel_gloc_ids' => '112,1031,1032,1075,1076,1077,1078,1079', 'currency' => 'KES', 'currency_name' => 'Kenyan Shilling', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Africa/Nairobi', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'ghana' => array( 'name' => 'Ghana', 'country_id' => '78', 'country_code' => 'gh', 'slug' => 'ghana', 'global_location_id' => '83', 'rel_gloc_ids' => '83,1033,1034,1072,1073,1074', 'currency' => 'GHS', 'currency_name' => 'Ghanaian Cedi', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Africa/Accra', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'ireland' => array( 'name' => 'Ireland', 'country_id' => '98', 'country_code' => 'ie', 'slug' => 'ireland', 'global_location_id' => '104', 'rel_gloc_ids' => '104,104,387,388,389,390,391,392,393,394,395,396,397,398,399,400,401,402,403,404,405,406,407,408,409,410,411,412,413,414,415,416', 'currency' => 'EUR', 'currency_name' => 'Euro', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/Dublin', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'vietnam' => array( 'name' => 'Vietnam', 'country_id' => '229', 'country_code' => 'vn', 'slug' => 'vietnam', 'global_location_id' => '234', 'rel_gloc_ids' => '234,1170,1171', 'currency' => 'VND', 'currency_name' => 'Vietnamese Dong', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Ho_Chi_Minh', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'cyprus' => array( 'name' => 'Cyprus', 'country_id' => '51', 'country_code' => 'cy', 'slug' => 'cyprus', 'global_location_id' => '55', 'rel_gloc_ids' => '55,1230,1231,1232,1233', 'currency' => 'EUR', 'currency_name' => 'Euro', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/Nicosia', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'malta' => array( 'name' => 'Malta', 'country_id' => '144', 'country_code' => 'mt', 'slug' => 'malta', 'global_location_id' => '134', 'rel_gloc_ids' => '134,1255,1254,1253,1252,1251,1250,1249,1248', 'currency' => 'EUR', 'currency_name' => 'Euro', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/Malta', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'maldives' => array( 'name' => 'Maldives', 'country_id' => '146', 'country_code' => 'mv', 'slug' => 'maldives', 'global_location_id' => '132', 'rel_gloc_ids' => '132,1172', 'currency' => 'MVR', 'currency_name' => 'Maldivian rufiyaa', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Indian/Maldives', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'turkey' => array( 'name' => 'Turkey', 'country_id' => '213', 'country_code' => 'tr', 'slug' => 'turkey', 'global_location_id' => '219', 'rel_gloc_ids' => '219,1173,1174,1175,1176', 'currency' => 'TRY', 'currency_name' => 'Turkish lira', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/Istanbul', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'thailand' => array( 'name' => 'Thailand', 'country_id' => '206', 'country_code' => 'th', 'slug' => 'thailand', 'global_location_id' => '213', 'rel_gloc_ids' => '213,1177', 'currency' => 'THB', 'currency_name' => 'Baht', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Bangkok', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'hong-kong' => array( 'name' => 'Hong Kong', 'country_id' => '91', 'country_code' => 'hk', 'slug' => 'hong-kong', 'global_location_id' => '97', 'rel_gloc_ids' => '97', 'currency' => 'HKD', 'currency_name' => 'Hong Kong dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Hong_Kong', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'germany' => array( 'name' => 'Germany', 'country_id' => '53', 'country_code' => 'de', 'slug' => 'germany', 'global_location_id' => '82', 'rel_gloc_ids' => '82,1178,1179,1180,1181,1182,1183,1184,1185,1186,1187', 'currency' => 'EUR', 'currency_name' => 'Euro', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Europe/Berlin', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'netherlands' => array( 'name' => 'Netherlands', 'country_id' => '157', 'country_code' => 'nl', 'slug' => 'netherlands', 'global_location_id' => '152', 'rel_gloc_ids' => '152,1188,1189,1190,1191,1192,1193', 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The certification tests the candidates on various areas in data mining and warehousing which include knowledge of planning, managing, designing, implementing, supporting, maintaining and analyzing the organization’s data warehouse and covering data mining and On-Line Analytical Processing (OLAP).<br /> <br /> <strong>Why should one take this certification?</strong><br /> This certification is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.<br /> Earning Vskills Data Mining and Warehousing Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.<br /> <br /> <strong>Who will benefit from taking this certification?</strong><br /> Job seekers looking to find employment in IT department of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.<br /> <br /> <strong>Companies that hire Vskills Certified Data Mining and Warehousing Professional</strong><br /> Data Mining and Warehousing professional are in great demand. Companies specializing in Integration Services are constantly hiring knowledgeable professionals. Various banks, telecom and IT companies also need data mining and warehousing professionals for data management and analysis.<br /> <br /> <strong>Table of Contents</strong><br /> <br /> <strong>DATA WAREHOUSING INTRODUCTION</strong> <ul> <li>Introduction</li> <li>Meaning of Data Warehousing</li> <li>History of Data Warehousing</li> </ul> <strong>DATA WAREHOUSING CHARACTERISTICS</strong> <ul> <li>Introduction</li> <li>Data Warehousing</li> <li>Operational vs. Informational Systems</li> <li>Characteristics of Data Warehousing</li> </ul> <strong>ONLINE TRANSACTION PROCESSING</strong> <ul> <li>Introduction</li> <li>Data Warehousing and OLTP Systems</li> <li>Processes in Data Warehousing OLTP</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional View s</li> <li>Benefits of OLAP</li> </ul> <strong>DATA WAREHOUSING MODELS</strong> <ul> <li>Introduction</li> <li>The Data Warehouse Model</li> <li>Data Modeling for Data Warehouses</li> </ul> <strong>DATA WAREHOUSING ARCHITECTURE</strong> <ul> <li>Introduction</li> <li>Structure of a Data Warehouse</li> <li>Data Warehouse Physical Architectures</li> <li>Principles of a Data Warehousing</li> </ul> <strong>DATA WAREHOUSING AND OPERATIONAL SYSTEMS</strong> <ul> <li>Introduction</li> <li>Operational Systems</li> <li>“ Warehousing” Data outside the Operational Systems</li> <li>Integrating Data from more than one Operational System</li> <li>Differences between Transaction and Analysis Processes</li> <li>Data is mostly Non-volatile</li> <li>Data saved for longer periods than in transaction systems</li> <li>Logical Transformation of Operational Data</li> <li>Structured Extensible Data Model</li> <li>Data Warehouse model aligns with the business structure</li> <li>Transformation of the Operational State Information</li> <li>De-normalization of Data</li> <li>Static Relationships in Historical Data</li> <li>Physical Transformation of Operational Data</li> <li>Operational terms transformed into uniform business terms</li> </ul> <strong>DATA WAREHOUSING CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Building a Data Warehouse</li> <li>Nine Decisions in the design of a Data Warehouse</li> </ul> <strong>DATA WAREHOUSING - APPLICATIONS</strong> <ul> <li>Introduction</li> <li>Data Warehouse Application</li> </ul> <strong>ROI AND DESIGN CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Need of a Data Warehouse</li> <li>Business Considerations: Return on Investment</li> <li>Organizational Issues</li> <li>Design Considerations</li> <li>Data content</li> <li>Metadata</li> <li>Data Distribution</li> <li>Tools</li> <li>Performance Considerations</li> </ul> <strong>TECHNICAL AND IMPLEMENTATION CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Technical Considerations</li> <li>Hardware Platforms</li> <li>Balanced Approach</li> <li>Optimal hardware architecture for parallel queryscalability</li> <li>Data warehouse and DBMS Specialization</li> <li>Communications Infrastructure</li> <li>Implementation Considerations</li> <li>Access Tools</li> </ul> <strong>DATA WAREHOUSING BENEFITS</strong> <ul> <li>Introduction</li> <li>Benefits of Data Warehousing</li> <li>Problems with Data Warehousing</li> <li>Criteria for a Data Warehouse</li> </ul> PROJECT MANAGEMENT PROCESS <ul> <li>Introduction</li> <li>Project Management Process</li> <li>The Scope Statement</li> <li>Project Planning</li> <li>Project Scheduling</li> <li>Software Project Planning</li> <li>Critical Path Method</li> <li>Decision Making</li> </ul> <strong>WORK BREAKDOWN STRUCTURE</strong> <ul> <li>Introduction</li> <li>Work Breakdow n Structure (WBS)</li> <li>How to build a WBS (a serving suggestion)</li> <li>To Create Work Breakdown Structure</li> <li>From WBS to Activity Plan</li> <li>Estimating Time</li> </ul> <strong>PROJECT ESTIMATION AND RISK</strong> <ul> <li>Introduction</li> <li>Project Estimation</li> <li>Analyzing Probability & Risk</li> </ul> <strong>MANAGING RISK</strong> <ul> <li>Introduction</li> <li>Risk Analysis</li> <li>Risk Management</li> <li>Risk Analysis</li> <li>Managing Risks: Internal & External</li> <li>Internal and External Risks</li> <li>Critical Path Analysis</li> </ul> <strong>DATA MINING CONCEPTS</strong> <ul> <li>Introduction</li> <li>Data Mining</li> <li>Data Mining Background</li> <li>Inductive Learning</li> <li>Statistics</li> <li>Machine Learning</li> </ul> <strong>DATA MINING AND KDD</strong> <ul> <li>Introduction</li> <li>What is Data Mining?</li> <li>Data Mining: Definitions</li> <li>KDD vs. Data Mining</li> <li>Stages OF KDD</li> <li>Machine Learning vs. Data Mining</li> <li>Data Mining vs. DBMS</li> <li>Data Warehouse</li> <li>Statistical Analysis</li> </ul> <strong>ELEMENTS OF DATA MINING</strong> <ul> <li>Introduction</li> <li>Elements and uses of Data Mining</li> <li>Relationships & Patterns</li> <li>Data Mining Problems/Issues</li> <li>Goals of Data Mining and Know ledge Discovery</li> </ul> <strong>DATA INFORMATION AND KNOWLEDGE</strong> <ul> <li>Data, Information and Knowledge</li> <li>What can Data Mining do?</li> <li>How does Data Mining Work?</li> <li>Data Mining in a Nutshell</li> </ul> <strong>DATA MINING MODELS</strong> <ul> <li>Data Mining</li> <li>Data Mining Models</li> <li>Discovery of Association Rules</li> <li>Discovery of Classification Rules</li> </ul> <strong>DATA MINING ISSUES AND CHALLENGES</strong> <ul> <li>Data Mining Problems/Issues</li> <li>Other Mining Problems</li> <li>Data mining Application Areas</li> <li>Data Mining Applications-Case Studies</li> <li>Housing Loan Prepayment Prediction</li> <li>Mortgage Loan Delinquency Prediction</li> <li>Crime Detection</li> <li>Store-Level Fruits Purchasing Prediction</li> <li>Other Application Area</li> </ul> <strong>DM NEAREST NEIGHBOR AND CLUSTERING TECHNIQUES</strong> <ul> <li>Types of Knowledge Discovered during Data Mining</li> <li>Comparing the Technologies</li> <li>Clustering And Nearest-Neighbor Prediction Technique</li> </ul> <strong>DECISION TREES</strong> <ul> <li>What is a Decision Tree?</li> <li>Decision Trees</li> <li>Where to use Decision Trees?</li> <li>Tree Construction Principle</li> <li>The Generic Algorithm</li> <li>Guillotine Cut</li> <li>Over Fit</li> </ul> <strong>DECISION TREES - ADVANCED</strong> <ul> <li>Best Split</li> <li>Decision Tree Construction Algorithms</li> <li>Cart</li> <li>ID3</li> <li></li> <li>Chaid</li> <li>How the Decision Tree Works</li> <li>State of the Industry</li> </ul> <strong>NEURAL NETWORKS</strong> <ul> <li>Basics of Neural Networks</li> <li>Are neural networks easy to use?</li> <li>Business Scorecard</li> <li>Where to use Neural Networks</li> <li>Neural Networks for Clustering</li> <li>Neural Networks for Feature Extraction</li> <li>Applications Score Card</li> <li>The General Idea</li> </ul> <strong>NEURAL NETWORKS - ADVANCED</strong> <ul> <li>What is a Neural Network Pparadigm?</li> <li>Design decisions in architecting a neural network</li> <li>Different types of Neural Networks</li> <li>Kohonen feature Maps</li> <li>Applications of Neural Networks</li> <li>Knowledge Extraction Through Data Mining</li> </ul> <strong>ASSOCIATION RULES AND GENETIC ALGORITHM</strong> <ul> <li>Association Rules</li> <li>Basic Algorithms for Finding Association Rules</li> <li>Association Rules among Hierarchies</li> <li>Negative Associations</li> <li>Additional Considerations for Association Rules</li> <li>Genetic Algorithm</li> <li>Crossover</li> <li>Genetic Algorithms In detail</li> <li>Mutation</li> <li>Problem-Dependent Parameters</li> <li>Encoding</li> <li>The Evaluation Step</li> <li>Data Mining using GA</li> </ul> <strong>OLAP MULTIDIMENSIONAL DATA MODEL</strong> <ul> <li>On Line Analytical Processing</li> <li>OLAP Example</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional Views</li> <li>Complex Calculations</li> <li>Time Intelligence</li> </ul> <strong>OLAP CHARACTERISTICS</strong> <ul> <li>Definitions of OLAP</li> 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The certification tests the candidates on various areas in data mining and warehousing which include knowledge of planning, managing, designing, implementing, supporting, maintaining and analyzing the organization’s data warehouse and covering data mining and On-Line Analytical Processing (OLAP).<br /> <br /> <strong>Why should one take this certification?</strong><br /> This certification is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.<br /> Earning Vskills Data Mining and Warehousing Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.<br /> <br /> <strong>Who will benefit from taking this certification?</strong><br /> Job seekers looking to find employment in IT department of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.<br /> <br /> <strong>Companies that hire Vskills Certified Data Mining and Warehousing Professional</strong><br /> Data Mining and Warehousing professional are in great demand. Companies specializing in Integration Services are constantly hiring knowledgeable professionals. Various banks, telecom and IT companies also need data mining and warehousing professionals for data management and analysis.<br /> <br /> <strong>Table of Contents</strong><br /> <br /> <strong>DATA WAREHOUSING INTRODUCTION</strong> <ul> <li>Introduction</li> <li>Meaning of Data Warehousing</li> <li>History of Data Warehousing</li> </ul> <strong>DATA WAREHOUSING CHARACTERISTICS</strong> <ul> <li>Introduction</li> <li>Data Warehousing</li> <li>Operational vs. Informational Systems</li> <li>Characteristics of Data Warehousing</li> </ul> <strong>ONLINE TRANSACTION PROCESSING</strong> <ul> <li>Introduction</li> <li>Data Warehousing and OLTP Systems</li> <li>Processes in Data Warehousing OLTP</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional View s</li> <li>Benefits of OLAP</li> </ul> <strong>DATA WAREHOUSING MODELS</strong> <ul> <li>Introduction</li> <li>The Data Warehouse Model</li> <li>Data Modeling for Data Warehouses</li> </ul> <strong>DATA WAREHOUSING ARCHITECTURE</strong> <ul> <li>Introduction</li> <li>Structure of a Data Warehouse</li> <li>Data Warehouse Physical Architectures</li> <li>Principles of a Data Warehousing</li> </ul> <strong>DATA WAREHOUSING AND OPERATIONAL SYSTEMS</strong> <ul> <li>Introduction</li> <li>Operational Systems</li> <li>“ Warehousing” Data outside the Operational Systems</li> <li>Integrating Data from more than one Operational System</li> <li>Differences between Transaction and Analysis Processes</li> <li>Data is mostly Non-volatile</li> <li>Data saved for longer periods than in transaction systems</li> <li>Logical Transformation of Operational Data</li> <li>Structured Extensible Data Model</li> <li>Data Warehouse model aligns with the business structure</li> <li>Transformation of the Operational State Information</li> <li>De-normalization of Data</li> <li>Static Relationships in Historical Data</li> <li>Physical Transformation of Operational Data</li> <li>Operational terms transformed into uniform business terms</li> </ul> <strong>DATA WAREHOUSING CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Building a Data Warehouse</li> <li>Nine Decisions in the design of a Data Warehouse</li> </ul> <strong>DATA WAREHOUSING - APPLICATIONS</strong> <ul> <li>Introduction</li> <li>Data Warehouse Application</li> </ul> <strong>ROI AND DESIGN CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Need of a Data Warehouse</li> <li>Business Considerations: Return on Investment</li> <li>Organizational Issues</li> <li>Design Considerations</li> <li>Data content</li> <li>Metadata</li> <li>Data Distribution</li> <li>Tools</li> <li>Performance Considerations</li> </ul> <strong>TECHNICAL AND IMPLEMENTATION CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Technical Considerations</li> <li>Hardware Platforms</li> <li>Balanced Approach</li> <li>Optimal hardware architecture for parallel queryscalability</li> <li>Data warehouse and DBMS Specialization</li> <li>Communications Infrastructure</li> <li>Implementation Considerations</li> <li>Access Tools</li> </ul> <strong>DATA WAREHOUSING BENEFITS</strong> <ul> <li>Introduction</li> <li>Benefits of Data Warehousing</li> <li>Problems with Data Warehousing</li> <li>Criteria for a Data Warehouse</li> </ul> PROJECT MANAGEMENT PROCESS <ul> <li>Introduction</li> <li>Project Management Process</li> <li>The Scope Statement</li> <li>Project Planning</li> <li>Project Scheduling</li> <li>Software Project Planning</li> <li>Critical Path Method</li> <li>Decision Making</li> </ul> <strong>WORK BREAKDOWN STRUCTURE</strong> <ul> <li>Introduction</li> <li>Work Breakdow n Structure (WBS)</li> <li>How to build a WBS (a serving suggestion)</li> <li>To Create Work Breakdown Structure</li> <li>From WBS to Activity Plan</li> <li>Estimating Time</li> </ul> <strong>PROJECT ESTIMATION AND RISK</strong> <ul> <li>Introduction</li> <li>Project Estimation</li> <li>Analyzing Probability & Risk</li> </ul> <strong>MANAGING RISK</strong> <ul> <li>Introduction</li> <li>Risk Analysis</li> <li>Risk Management</li> <li>Risk Analysis</li> <li>Managing Risks: Internal & External</li> <li>Internal and External Risks</li> <li>Critical Path Analysis</li> </ul> <strong>DATA MINING CONCEPTS</strong> <ul> <li>Introduction</li> <li>Data Mining</li> <li>Data Mining Background</li> <li>Inductive Learning</li> <li>Statistics</li> <li>Machine Learning</li> </ul> <strong>DATA MINING AND KDD</strong> <ul> <li>Introduction</li> <li>What is Data Mining?</li> <li>Data Mining: Definitions</li> <li>KDD vs. Data Mining</li> <li>Stages OF KDD</li> <li>Machine Learning vs. Data Mining</li> <li>Data Mining vs. DBMS</li> <li>Data Warehouse</li> <li>Statistical Analysis</li> </ul> <strong>ELEMENTS OF DATA MINING</strong> <ul> <li>Introduction</li> <li>Elements and uses of Data Mining</li> <li>Relationships & Patterns</li> <li>Data Mining Problems/Issues</li> <li>Goals of Data Mining and Know ledge Discovery</li> </ul> <strong>DATA INFORMATION AND KNOWLEDGE</strong> <ul> <li>Data, Information and Knowledge</li> <li>What can Data Mining do?</li> <li>How does Data Mining Work?</li> <li>Data Mining in a Nutshell</li> </ul> <strong>DATA MINING MODELS</strong> <ul> <li>Data Mining</li> <li>Data Mining Models</li> <li>Discovery of Association Rules</li> <li>Discovery of Classification Rules</li> </ul> <strong>DATA MINING ISSUES AND CHALLENGES</strong> <ul> <li>Data Mining Problems/Issues</li> <li>Other Mining Problems</li> <li>Data mining Application Areas</li> <li>Data Mining Applications-Case Studies</li> <li>Housing Loan Prepayment Prediction</li> <li>Mortgage Loan Delinquency Prediction</li> <li>Crime Detection</li> <li>Store-Level Fruits Purchasing Prediction</li> <li>Other Application Area</li> </ul> <strong>DM NEAREST NEIGHBOR AND CLUSTERING TECHNIQUES</strong> <ul> <li>Types of Knowledge Discovered during Data Mining</li> <li>Comparing the Technologies</li> <li>Clustering And Nearest-Neighbor Prediction Technique</li> </ul> <strong>DECISION TREES</strong> <ul> <li>What is a Decision Tree?</li> <li>Decision Trees</li> <li>Where to use Decision Trees?</li> <li>Tree Construction Principle</li> <li>The Generic Algorithm</li> <li>Guillotine Cut</li> <li>Over Fit</li> </ul> <strong>DECISION TREES - 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The certification tests the candidates on various areas in android application development which includes knowledge of android framework, screen layout, UI design, events, intents and widgets.<br /> Knowledge of Java is prerequisite for the certification.<br /> <br /> <strong>Why should one take this certification?</strong><br /> This certification is intended for professionals and graduates wanting to excel in their chosen areas. 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Come build a rewarding, meaningful career working with the best and brightest people in technology at Canonical, a growing international software company. </p><p> Canonical's Store team develops and operates a large system of backend services that power the Snap Store and Charmhub.io marketplaces. Our services are built primarily in Python, with a bit of Golang. </p><p> We have some exciting challenges ahead including continuing to scale our production architecture, significantly expanding the range of software we can deliver through the system powering our marketplaces, and enhancing our offering for the booming world of IoT and for large Enterprise solutions. </p><p> If you have a passion for clean APIs, have a bias towards shipping, and believe that automated tests are the key to higher velocity and reliability, you'll fit right in. </p><h3> What you'll do </h3><ul><li> Collaborate remotely with a globally distributed team. </li><li> Write clean web service APIs to support both CLI and web frontend clients, using Python (and optionally Golang). </li><li> Design and implement new features and enhancements from spec to production and ongoing operations at scale. </li><li> Review code and technical designs produced by other engineers. </li><li> Discuss ideas and collaborate on finding good solutions. </li><li> Work remotely with global travel for 2 to 4 weeks for internal and external events. </li></ul><h3> Who you are </h3><ul><li> You have demonstrated professional proficiency in developing public-facing APIs and web applications using Python. </li><li> You have a broad technology base but favour backend code and infrastructure. </li><li> You know your way around relational and non-relational databases and can effectively design data models that perform well, and tune queries to access them. </li><li> You are comfortable with Ubuntu as a development and deployment platform. </li><li> You have demonstrated strong academic performance in Computer Science, STEM or a similar degree. </li><li> You love technology and working with a diverse set of talented people. </li><li> You are curious, flexible, articulate, and accountable. </li><li> You value soft skills and are passionate, enterprising, thoughtful, and self-motivated. </li></ul><h3> About Canonical </h3><p> Canonical is a growing, international software company that works with the open-source community to deliver Ubuntu -- the world's #1 cloud operating system. Our mission is to realise the potential of free software in the lives of individuals and organisations. Our services are helping businesses worldwide to reduce costs, improve efficiency and enhance security with Ubuntu. Canonical is a unique tech company - global, remote-first, open source, with 700 professionals across 50 countries - we want to be the world's best, not biggest, global software company. With almost every team remote by default, Canonical sets the pace on the 21st-century digital workplace. </p><h3> What Canonical offers: </h3><ul><li> Work from home </li><li> Learning and development allowances </li><li> Competitive salary </li><li> Annual compensation review </li><li> Recognition rewards </li><li> Generous annual leave </li><li> Paid maternity, paternity and sick leave </li><li> Priority Pass for travel </li><li> Exposure to international business and technology </li></ul><p><em> We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. 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