About AI

• John McCarthy, the father of AI, who coined the term in 1956, defines it as "the science and engineeringg of making intelligent machines."

Types of AI

• Weak AI: IBM considers self-driving cars and virtual assistants such Siri under the category of Weak AI.
• General AI: Those applications where machines emulate human capabilities and perform any task just like a human.
• Strong AI: It's when machines develop consciousness and decision-making on par (or better) than humans.

About Big Data

• The International Telecommunication Union (ITU) defines BD as “a paradigm for enabling the  Collection, storage, management, analysis and visualisation, potentially under real-time constraints, of extensive datasets with  heterogeneous characteristics”.

Characteristics of BD

BD is characterised by the 4 “Vs

• Variety: Structured, unstructured and semistructured data that are gathered from multiple sources.
• Veracity: Biases, noise and abnormality in data.
• Velocity: How fast data is being collected and how fast data is processed by big data technologies to deliver the expected results.
• Volume: The large volumes of data that are generated on a daily basis from various sources.

Categories of BD

• Structured data
• Semi-structured data
• Unstructured data

Types of big data

• Metadata (data about data)
• Data exhaust
• Human-sourced (citizen-generated) data
• AI-sourced data
• Personal data
• Non-personal data (NPD)
• Open data

Big Data Analytics

• Data Collection
• Data Pre-processing and Analysis.
• Big Data Analytics platforms and tools.

BD in Telecom

• Network Infrastructure: Network Events, Call records (on and off network), Number of text and multimedia messages, Volume of data Traffic, Location-specific Data, User handset data.
• Product: Product catalogue, Product life-cycle Data, Product and platform costs, Innovation roadmap, Product usage.
• Marketing & Sales: Customer Devices, Option preferences, Sales channel data, Segmentation data
• Customer Care: Order data, Contact data, Fault handling Data.

Opportunities for Telecom Sector

• Enhancing Overall Quality of Service (QoS)
• Spectrum management
• Network Security
• Customer Centric
• Broadcasting sector