INTRODUCTION TO DATA ANALYTICS & CYBERSECURITY

This program develops foundational skills in using production data and handling workplace information securely in smart manufacturing. Learners practise correcting production records, interpreting reports, communicating findings, and responding safely to workplace data scenarios. Successful completion requires written practical work and an oral explanation that together provide sufficient evidence of foundational competence against the course performance objectives.

Issuer	EMC
Issued On	1789560000
Expires	-

Badge assertion is valid

Badge has not been revoked

Badge has not expired

Check that the badge was awarded to the correct recipient by entering their email address:

Validate another badge

{"proof":[{"type":"DataIntegrityProof","verificationMethod":"did:key:z6MkuqG92C7BzdGBQRoCZi5R34RMfkdtsLtuEomGa5VgZfFL#z6MkuqG92C7BzdGBQRoCZi5R34RMfkdtsLtuEomGa5VgZfFL","created":"2026-09-16T14:22:35Z","proofValue":"z4HLbp8rybH3MYBpxSnyhiN51FE7Ygcotx69WBvEFUUEiVpyD5xboXPH1HVsZTjpvAAmHGEvD6sNpsVjRHymkNGG7","cryptosuite":"eddsa-rdfc-2022","proofPurpose":"assertionMethod"}],"credentialSubject":{"achievement":{"description":"This program develops foundational skills in using production data and handling workplace information securely in smart manufacturing. Learners practise correcting production records, interpreting reports, communicating findings, and responding safely to workplace data scenarios. Successful completion requires written practical work and an oral explanation that together provide sufficient evidence of foundational competence against the course performance objectives.\n\n","inLanguage":"en","type":["Achievement"],"id":"https://factory.cancred.ca/obv3/achievements/TLF680a1OIJ7aGB?cid=427b7ef00842a9f7cd11471d7adf37f123b1471990a562fcfe44c863d9232bd5&lang=en","criteria":{"narrative":"The learner successfully completes the Session 4 final assessment, including both written practical work and an oral explanation. The instructor considers the combined evidence against the course performance objectives and awards a Pass when it demonstrates foundational competence: accurate record handling, evidence-based interpretation and decisions, clear communication of findings, and safe handling of workplace data, with little to no error and little to no supervision. Passing Session 4 means passing the course.\n\n**Course Content** \n\n-  Production records: spreadsheet layout, consistent units, traceability, and correction of missing, duplicate or impossible values.\n-  Production and quality reports: defect summaries, trends, normal variation, and signals that warrant monitoring or escalation.\n-  Supervisor-ready summaries: checking findings against source data and explaining what happened, why it matters and what happens next.\n-  Secure data handling: Green, Yellow and Red classification, approved destinations, and appropriate boundaries for external AI tools.\n-  Workplace data scenarios: recognizing suspicious requests and choosing when to refuse, verify, report or escalate.\n-  AI-supported learning: Gemini Notebook is introduced in Session 1 and used throughout the course to support learning and review of course material.\n-  Integrated practice and assessment: Sessions 1–3 prepare learners to apply these skills in the written practical task and oral explanation in Session 4.\n\n**Learning Outcomes**\n\n*Record and Organize Production Data*\n\n-  Enter production data into a spreadsheet with sound layout and consistent units.\n-  Maintain clear attribution and traceability when entering or correcting production records.\n-  Find and fix duplicates, missing values, and impossible values.\n\n*Read and Act on Production and Quality Reports*\n\n-  Explain in plain language what a defect summary, trend chart, or SPC (statistical process control) chart shows.\n-  Distinguish normal variation from a signal that needs attention.\n-  Decide whether to leave it, keep watching, or escalate — and to whom.\n\n*Turn Raw Data into Supervisor-Ready Summaries*\n\n-  Consolidate a small raw dataset into a chart or one-page summary.\n-  Verify spreadsheet-suggested insights against the data before using them.\n-  State findings as decisions: what happened, why it matters, what next.\n-  Prepare a data summary that supports a Lean improvement decision.\n\n*Handle Production Data Securely*\n\n-  Classify data before it moves into three sensitivity tiers — Green, Yellow, Red — using a simple traffic-light scheme built for the plant.\n-  Decide where data may travel and what never leaves the plant.\n-  Answer “can I just dump this into ChatGPT?” correctly for a given dataset.\n-  Know what data is safe to use with external AI (e.g., ChatGPT).\n\n*Respond to Workplace Data Scenarios*\n\n-  Choose and justify a response: report, refuse, verify, or escalate.\n-  Recognize suspicious data requests or attachments dressed as routine work.\n-  Trace one piece of data end to end: recorded, read, summarized, secured.\n\n\n\n**Minimum requirements**\n\n-  Complete the written practical component of the final assessment. Practical evidence must be attributable to the learner; any instructor-accepted alternative or directly observed work must be documented.\n-  Complete the oral component of the final assessment, explaining and justifying the record correction, report decision and safe workplace response.\n-  Meet the qualitative passing criteria through the combined written practical and oral evidence. A missing required component leaves the assessment incomplete.\n\n*Estimated effort time*\n\n12 hours\n\n*EMC updates learning content on a regular basis. Version: 2026-1*\n\n\n\n\n\n\n\n","id":"https://factory.cancred.ca/v1/badge/_/TLF680a1OIJ7aGB/criteria.html?v=2.0&c_id=427b7ef00842a9f7cd11471d7adf37f123b1471990a562fcfe44c863d9232bd5"},"tag":["Cybersecurity","DataAnalytics","DataQuality","ProductionData","ResponsibleAI","SmartManufacturing"],"image":{"id":"https://factory.cancred.ca/obv3/images/badge/427b7ef00842a9f7cd11471d7adf37f123b1471990a562fcfe44c863d9232bd5","type":"Image"},"name":"INTRODUCTION TO DATA ANALYTICS & CYBERSECURITY"},"type":["AchievementSubject"],"identifier":[{"salt":"ZEIoDBZidp","type":"IdentityObject","hashed":true,"identityType":"emailAddress","identityHash":"sha256$939d356104eda8ee5e8f33d0dcf72f1e2872b6c4f8df3debcb5c2652b6fcb39a"}]},"endorsement":[],"validFrom":"2026-09-16T13:15:14Z","type":["VerifiableCredential","OpenBadgeCredential"],"id":"https://factory.cancred.ca/obv3/credentials/97e7e2ab45638626815e24aa40125e7649087587","credentialStatus":{"type":"1EdTechRevocationList","id":"https://factory.cancred.ca/obv3/revoked/QPISN0aV773aKK/TLF680a1OIJ7aGB"},"issuer":{"name":"EMC","image":{"type":"Image","id":"https://factory.cancred.ca/obv3/images/issuer/QPISN0aV773aKK"},"otherIdentifier":[{"identifierType":"systemId","type":"IdentifierEntry","identifier":"QPISN0aV773aKK"}],"email":"info@emccanada.org","description":"EMC is a unique Canadian not-for-profit organization dedicated to helping manufacturers grow and become more competitive. Our education, training and development programs build excellence at all levels and every stage of a career.\r\n\r\nEMC est un organisme canadien sans but lucratif unique en son genre, qui se consacre à aider les fabricants à croître et à devenir plus concurrentiels. Nos programmes d’éducation, de formation et de perfectionnement favorisent l’excellence à tous les niveaux et à chaque étape d’une carrière.","url":"https://www.emccanada.org/","id":"did:key:z6MkuqG92C7BzdGBQRoCZi5R34RMfkdtsLtuEomGa5VgZfFL","type":["Profile"]},"awardedDate":"2026-09-16T13:15:14Z","@context":["https://www.w3.org/ns/credentials/v2","https://purl.imsglobal.org/spec/ob/v3p0/context-3.0.3.json","https://purl.imsglobal.org/spec/ob/v3p0/extensions.json"]}