week06
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week06 [2021/07/19 06:20] – created suhaw | week06 [2021/07/22 06:29] (current) – [Ghorra Paul] suhaw | ||
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+ | ===== Thursday 22 July 2021 ===== | ||
+ | |||
+ | |||
+ | |||
+ | ==== elearning - Introduction to Business Analytics ==== | ||
+ | |||
+ | ==== John David Ariansen and Madecraft ==== | ||
+ | |||
+ | |||
+ | Data sources: | ||
+ | * Internal | ||
+ | * Sales | ||
+ | * Breakdown to: demographics, | ||
+ | * Cost | ||
+ | * Fixed | ||
+ | * Variable | ||
+ | * Marketing | ||
+ | * Psychometric | ||
+ | * External | ||
+ | * Market Reports | ||
+ | * Market players | ||
+ | * Size of market | ||
+ | * High-level data points | ||
+ | * Market Research | ||
+ | * Behavourial patterns | ||
+ | * Buyer personas | ||
+ | |||
+ | |||
+ | Data governance: ensure quality of data assets | ||
+ | |||
+ | Causes of data quality issues: | ||
+ | * Data collection: Manual, lack of index field | ||
+ | * System integration (different data format across systems) | ||
+ | * Missing data | ||
+ | |||
+ | Tools/ | ||
+ | * Sales: Square, Stripe, Clover | ||
+ | * Cost: Quickbooks | ||
+ | * Marketing: Google Analytics, Salesforce | ||
+ | * Psychometric: | ||
+ | |||
+ | Data Management tools: | ||
+ | * MS Excel | ||
+ | * Tableau | ||
+ | * PowerBI | ||
+ | * MS SQL Server | ||
+ | |||
+ | |||
+ | |||
+ | ==== Ghorra Paul ==== | ||
+ | |||
+ | BCG Report " | ||
+ | |||
+ | Shipping container routing: https:// | ||
+ | |||
+ | Key takeaways: | ||
+ | * Gathering relevant data and preparing it for analysis is often the longest step of analysis | ||
+ | * Make it visible - Just visualising existing data can already unlock tremendous value | ||
+ | * Simulation: A digital twin can expedite learning with risk free experimentation | ||
+ | * ML: Input data determines strength of the algorithm - it cannot predict outcomes it hasn't seen | ||
+ | * 3 step framework - Decision variables, Objective, Constraint, help to frame optimisation problem | ||
+ | |||
+ | |||
+ | ===== Wednesday 21 July 2021 ===== | ||
+ | |||
+ | |||
+ | ==== e-learning - Digital Enablers - AI, IoT, Cybersecurity, | ||
+ | |||
+ | === AI === | ||
+ | |||
+ | * Symbolic Reasoning/ | ||
+ | * Abstract problems, but know steps | ||
+ | * Machine Learning | ||
+ | * Look for patterns | ||
+ | * Artificial neural networks | ||
+ | |||
+ | == Approaches == | ||
+ | |||
+ | * Match patterns | ||
+ | * Data vs reasoning | ||
+ | * Unsupervised learning | ||
+ | * Machines creates categories based on similarities it detects, may be different from human categories | ||
+ | * Deep learning | ||
+ | * Clustering | ||
+ | * Backpropagation | ||
+ | * Allows later feedback to go back and adjust earlier rules/ | ||
+ | * Regression | ||
+ | |||
+ | |||
+ | === IoT === | ||
+ | |||
+ | |||
+ | == Business View == | ||
+ | |||
+ | * Software-defined product | ||
+ | * Hardware-defined product | ||
+ | * Network fabric | ||
+ | * External system interface | ||
+ | |||
+ | |||
+ | == Software-defined product == | ||
+ | |||
+ | * Cyber Model | ||
+ | * digital simulation of the product' | ||
+ | * represented by statistics | ||
+ | * Application | ||
+ | * Functionality | ||
+ | * Human interface | ||
+ | * Data interface | ||
+ | |||
+ | * IoT value modeling | ||
+ | |||
+ | |||
+ | == Hardware-defined product == | ||
+ | * Connected sensors and actuators | ||
+ | * sensor gathers data | ||
+ | * transducer | ||
+ | * actuators makes physical changes | ||
+ | * Embedded system | ||
+ | * gathers data | ||
+ | * packages data | ||
+ | * sends data (over the OT Network) to application | ||
+ | * may also process application, | ||
+ | |||
+ | * Mist computing vs cloud computing | ||
+ | |||
+ | == Network fabric == | ||
+ | |||
+ | * OT (Operational technology) network | ||
+ | * IT network | ||
+ | * Backhaul | ||
+ | * Internet (public cloud) | ||
+ | * Product cloud (private) | ||
+ | |||
+ | * IoT protocol | ||
+ | * Payload: data from sensors | ||
+ | * Application protocol: provides info context to payload | ||
+ | * Network protocol: data info to move it along its path | ||
+ | * Media protocol: allows it to be sent over the air | ||
+ | |||
+ | == External system interface == | ||
+ | |||
+ | * Analytics | ||
+ | * Data services | ||
+ | * Business systems | ||
+ | * Other IoT products | ||
+ | |||
+ | |||
+ | |||
+ | === Cybersecurity === | ||
+ | |||
+ | * Many different types of cybersecurity breaches | ||
+ | * Phishing | ||
+ | * Malware | ||
+ | * DDoS | ||
+ | * Brute force attack | ||
+ | * Physical breach | ||
+ | * Financial and reputation harm | ||
+ | * Cybersecurity spending growths 10x slower than number of attacks | ||
+ | * Getting the people part is critical | ||
+ | * People account for 72% of breaches | ||
+ | |||
+ | |||
+ | === DDP: Data & Digital Platform === | ||
+ | |||
+ | * Company' | ||
+ | * Identify concrete and profitable use cases to fund the long-term and incremental transformation | ||
+ | * Build data driven organisation to enable use cases | ||
+ | * NG architecture to migrate legacy business logic and data incrementally onto new digital and data platform | ||
+ | * Master key technologies such as datalake, fueled by legacy and new data sources | ||
+ | * Governance, Organisation, | ||
+ | |||
+ | === Cloud === | ||
+ | |||
+ | Shift to the cloud driven by changes in technology economics | ||
+ | * Changes are here to stay | ||
+ | |||
+ | Different possibilities to leverage cloud services: choose wisely | ||
+ | * Infrastructure | ||
+ | * Platform | ||
+ | * Software | ||
+ | * Business Processes | ||
+ | |||
+ | Potential to reduce TCO | ||
+ | * Don't forget Maintenance, | ||
+ | |||
+ | Hyperscalability for the future | ||
+ | * Reduces upfront costs for uncertain initiatives | ||
+ | * Allows scalability for wildly successful ones | ||
+ | * Can scale back if the fad has passed | ||
===== Monday 19 July 2021 ===== | ===== Monday 19 July 2021 ===== | ||
+ | |||
+ | |||
+ | ==== Grantly Mailes ==== | ||
+ | |||
+ | === Data and Digital Disruption === | ||
+ | |||
+ | Technological Ages | ||
+ | * Desktop: MS | ||
+ | * Internet: Amazon, Google | ||
+ | * Mobile | ||
+ | * Data | ||
+ | |||
+ | * Artificial Intelligence: | ||
+ | * Internet of Things (IoT) | ||
+ | * Blockchain | ||
+ | * https:// | ||
+ | * Data and Digital platform | ||
+ | * Data Lakes is next-gen Data Warehouses | ||
+ | * (frm Google) A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. | ||
+ | * Cloud Computing | ||
+ | * Cybersecurity | ||
+ | |||
+ | |||
+ | |||
+ | |||
+ | === Digital Transformation: | ||
+ | |||
+ | Strategy and Purpose | ||
+ | * Purpose | ||
+ | * Human potential | ||
+ | * Organisation | ||
+ | * Ecosystem | ||
+ | * Societal | ||
+ | * Customer centric | ||
+ | |||
+ | Outcomes | ||
+ | * Customer | ||
+ | * Operational | ||
+ | * New offers/ | ||
+ | |||
+ | |||
+ | |||
+ | Human | ||
+ | |||
+ | |||
+ | |||
+ | Technology: Data and Digital Platform | ||
+ | |||
+ | |||
+ | BCG-KLM Partnership: | ||
+ | |||
==== e-Learning ==== | ==== e-Learning ==== | ||
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* Identify outgrowths | * Identify outgrowths | ||
* Refresh plans frequently | * Refresh plans frequently | ||
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week06.1626675647.txt.gz · Last modified: 2021/07/19 06:20 by suhaw