What is the advantage of using a graphical approach to define data flow in Azure Data Factory?

Enables configuring data sources and transformations visually without writing code.

Writing complex code for data manipulation.

Using APIs to connect to data sources.

How can you retrieve data that was accidentally deleted from an Azure Data Factory data source?

By writing custom code to scan the data source.

There is no way to retrieve deleted data in Azure Data Factory.

Restoring the data source from a backup.

Using the graphical interface to recover the data.

What are the two main types of data sources that can be used in an Azure Data Factory?

Structured and unstructured data sources

Cloud and on-premises data sources

Real-time and historical data sources

Relational and non-relational data sources

What is the purpose of data transformation in an Azure Data Factory?

To define the flow of data between sources and destinations.

To modify and clean data before loading it into a destination.

To compress data for storage optimization.

To connect to different data sources.

How does Azure Data Factory automatically generate Spark code?

By converting the graphical data flow logic into Spark code.

Through machine learning algorithms that analyze data flow patterns.

By requiring users to write Spark code manually.

By leveraging pre-built connectors for different data sources.

What are some of the benefits of using Azure Data Factory for data flow automation?

Reduced development time, improved accuracy, and simplified maintenance.

Data Factory cannot automate data transformations.

Manual configuration is still required for complex data flows.

Increased complexity, higher costs, and vendor lock-in.

What is the difference between Data Factory and Data Flow activity?

Data Factory is a service for managing and orchestrating data pipelines, while Data Flow activity is a specific activity used within Data Factory to move data.

Data Factory is for real-time data processing, while Data Flow is for batch data processing.

There is no difference, they are the same thing.

Data Flow is a separate service for cloud-based data integration.

How can you connect Azure Data Factory to on-premises data sources?

By using self-hosted integration runtime.

By deploying Data Factory agents on-premises.

Through virtual private networks (VPNs).

Data Factory cannot connect to on-premises data sources.

What are some of the common use cases for Azure Data Factory?

ETL (Extract, Transform, Load) processes, data warehousing, and data lake creation.

Real-time data analytics, machine learning model training, and data visualization.

Data governance, data lineage tracking, and data quality monitoring.

Data encryption, data security, and access control.

Data flow in Azure data factory

Filter Transformation in Mapping Data Flow in Azure Data Factory

Conditional Split Transformation in Mapping Data Flow in Azure data factory

How to use Aggregate Transformation in Mapping Data Flow in Azure Data Factory

Mapping Data Flow Debug Mode in Azure Data Factory

Azure Data Factory - Tips to name partitioned files as column data in data flow

Prepare a question paper mcq and descriptive of following syllabus Kotlin basics: Introduction to Kotlin, Benefits of using Kotlin, Use Kotlin REPL to practice basic expressions, Control flow statements in Kotlin, Null safety with Kotlin. Functions: Creating and calling functions with default and named arguments, Writing concise and compact functions, Passing functions as arguments to other functions, Writing simple lambdas. Classes and Objects: Introduction to object-oriented programming in Kotlin, Classes and objects in Kotlin, Constructors, Visibility modifiers, Subclasses and inheritance, Interfaces, Data classes, Singleton class enums, Pairs, triples and collections in Kotlin, Extensions in Kotlin Buildind first Android app: Installing Android Studio, Creating an Android app project, Deploying the app to an emulator or a device, Building an Android app that contains images and a click handler, Modifying views within the layout of an app, Adding libraries to module gradle file. Layouts: Creating layouts in Android Studio using XML and the Layout Editor, Adding interactivity to your app, Working with ConstraintLayout, Data binding basics App Navigation: Creating Fragments, Defining NavHostFragment, navigation graphs, navigational paths, Functionality of Back and Up buttons, Defining the options menu, Creating a navigational drawer, Using the Safe Args plugin and passing of arguments,Starting an external Activity Activity and Fragment Lifecycles: Understanding Activity and Fragment Lifecycles, Exploring logging options in your app, Using the Android Lifecycle library, Exploringconfiguration changes App Architecture (UI Layer) : Using the recommended Android App Architecture, Using the LifeCycle, ViewModel, and ViewModelFactory classes, Adding LiveData and LiveData, observers, Adding Data Binding with ViewModel and LiveData, Adding LiveData , transformation Connect to the Internet: Connecting to a web service with the Retrofit library, Parsing aJSON response with the Moshi library, Using coroutines with Retrofit , Loading and displaying images from the Internet, Filtering data from the Internet. Repository pattern and Work Manager: Adding an offline cache and repository,Implementing Work Manager, Working with background workers and periodic Worker Request App UI Design: Introduction to basic app design, Understanding Styles and Themes, Implementing Material Design, Designing for everyone

New Trends in Agriculture Extension approaches Extension has been, and still is, under attack from a wide spectrum of politicians and economists over its cost and financing. As a result, Extension Systems have had to make changes, by restating the system’s mission, developing a new vision for the future, and formulating plans for the necessary transition to achieve the desired change. 1. Privatization of Agricultural Extension Service Privatization: Process of funding and delivering the extension services by private individual or organization is called Private Extension. Concept: Privatization of extension refers to services rendered in rural area & allied aspects of extension personnel working in private agencies or organization for which farmers are expected to pay a fee & it can be viewed as supplementary or alternative to public extension services (Sarvanan & Shivalinge 1980). Privatization approaches ➢ Share cropping system ➢ Village extension contract system ➢ Public extension through private delivery ➢ Service for vouchers Strengths of Private Extension System ➢ More demand - driven rather than supply – driven ➢ High quality of services in terms of satisfying information needs of clientele, trained manpower, sustained finances and resource allocation ➢ Provides for an information mix and choices available to farmers ➢ Enhanced efficiency of staff ➢ Assure continuous supply and quality agricultural products ➢ More effective because farmer can select an adviser who is the best able to help ➢ Healthy competition among service provider will lead to better quality and lower costs for service Weakness of Private Extension System ➢ Concentrate on area having favorable physical environment ➢ More face-to-face contacts (person oriented) ➢ Increased dependence of farmers and hence exploitation ➢ No education role ➢ Deprivation of small farmers ➢ Hamper the free flow of information 2. Cyber Extension or e-extension Concepts Cyber space: it is the imaginary or virtual space of computers connected with each other on Networks, across the Globe. Cyber extension: it means 'using the power of online networks, computer communications and digital interactive multimedia to facilitate dissemination of agriculture technology. Cyber Extension thus can be defined as the extension over cyber space. Important tools of cyber extension E-Mail, Telnet, File Transfer Protocol (FTP), Gopher, Archie and World Wide Web (WWW) Strengths of Cyber Extension ➢ Access to the astounding information and continuously available ➢ Information rich and instantaneously available of information ➢ Interactive communication ➢ The information is available from any point on the globe ➢ Communication is dynamic ➢ Cut steps from traditional process ➢ Save money, time and effort ➢ Multiplicity of purpose Issues and Concerns of Cyber Extension ➢ Lack of Reliable Telecom Infrastructure in Rural Areas ➢ Erratic or no Power Supply ➢ Lack of ICT Trained manpower (willing to serve) in Rural Areas ➢ Lack of content (locally relevant and in local languages) ➢ Lack of Information Services to Rural Clientele ➢ Low Purchasing power of the Rural communities ➢ Lack of Holistic Approaches ➢ Issues of Sustainability Application of cyber extension ➢ Village information shops Dr. M.S. SwaminathanResearch Foundation, Chennai ➢ Information villagers MANAGE in Ranga Reddy District in Andhra pradesh ➢ Gyandoot net initiative of District Dhar, Madhya Pradesh. ➢ Warna wired village of National Informatics Center (NIC) in Kolhapur- Sangli Districts of Maharashtra 3. Market-Led-Extension (MLE) Concepts Market: A congregation of prospective buyers & sellers with a common motive of trading a particular commodity. Extension: It is the spreading/reaching out to the mass Market-led-extension: Agriculture & economics coupled with extension is the perfect blend for reaching at the door steps of common man with the help of technology. Dimensions of market-led extension ➢ Marketing mix: A planned mix of the controllable elements of a product's marketing plan commonly termed as 4Ps: product, price, place, and promotion. These four elements are adjusted until the right combination is found that serves the needs of the product's customers, while generating optimum income. ➢ Marketing plan: A marketing plan is a comprehensive document that outlines a business and marketing efforts for the coming year. It describes business activities involved in accomplishing specific marketing objectives within a set time frame. A marketing plan also includes a description of the current marketing position of a business, a discussion of the target market and a description of the marketing mix that a business will use to achieve their marketing goals. ➢ Market Intelligence: It is the information relevant to a company’s markets, gathered and analyzed specifically for the purpose of accurate and confident decision making. Market intelligence includes the process of gathering data from the company’s external environment, whereas the business intelligence process is primarily based on internal recorded events – such as sales, shipments and purchases. ➢ Market oriented production ➢ Use of Technology Strengths of market-led extension ➢ SWOT analysis of the market ➢ Organization of Farmers’ Interest Groups (FIGs) ➢ Enhancing the interactive and communication skills of the farmers ➢ Establishing marketing and agro-processing linkages ➢ Advice on product planning ➢ Educating the farming community ➢ Direct marketing ➢ Acquiring complete market intelligence ➢ Publication of agricultural market information Production of video films of success stories ➢ Challenges to market-led extension ➢ Gigantic size of extension system ➢ Information technology Diverse conditions ➢ Market intelligence ➢ Reforms in agricultural extension system Government Initiatives ➢ Central warehousing Corporation-1965 ➢ MSP by Commission for Agricultural Cost and Price (CACP) ➢ Food Corporation of India ➢ Then some others as: Cotton Corporation of India (CCI), Jute Corporation of India (JCI), National Dairy Development Board (NDDB), Agriculture and Processed food Export Development Authority (APEDA) etc. 4. Farmer--Led-Extension (FLE) Farmer--led-extension is defined as 'the provision of training by farmers to farmers, often through the creation of a structure of farmer promoters and farmer trainers' (Scarborough et al., 1997). Philosophy and principles ➢ Farmers and local institutions (e.g. producer organizations or village leaders) should play a key role in selecting farmer-trainers and monitoring and evaluating them. This helps make the programmes more accountable to the community or groups that they serve. ➢ Farmer-trainers are ‘of the community’; they communicate in local languages and are more sensitive to local cultures, mannerisms, farming practices, and farmers’ needs. ➢ Farmer-trainers should be selected on the basis of their skills and interest in sharing information, not just on their farming expertise. ➢ Farmer-trainers need strong linkages with and support from development agents (whether government, non-government organization (NGO), or private), the people who train and backstop them. Farmer-trainers generally serve as a complement to existing extension systems, rather than being a substitute for them. ➢ Facilitating organizations and local institutions need to be proactive in ensuring that women as well as men become farmer-trainers. ➢ Simple and appropriate reference materials should be made available to the farmer trainers. Essential Elements of Farmer--led-extension ➢ The group ➢ The Field ➢ The Facilitator ➢ The curriculum ➢ Programme leader ➢ Financing Special features of Farmer--led-extension ➢ All learning is field based & it is primary venue for learning ➢ FLE group learning constantly over the experimentation period ➢ FLE promotes healthy decisions & quality decisions ➢ Farmers conduct their own field studies with comparisons or treatments ➢ Facilitates Farmer-to-Farmer communication ➢ Field staff serve as facilitators ➢ FLE is a unique way to educate farmers ➢ It is an effective platform for sharing of experiences and collectively solving agriculture related problems. 5. Expert system Expert system is an intelligent computer program that uses knowledge and inferences procedures to solve problems (Daniel Hunt, 1986). Objectives of developing expert system ➢ To enhance the performance of agricultural extension personnel and farmer ➢ To make farming more efficient and profitable ➢ To reduce the time required in solving the problems ➢ To maintain the expert system by continuously upgrading the database Advantages of expert system ➢ Solves critical problems by making logical deductions without taking much time ➢ It combines experimental and conventional knowledge with the reasoning skills of specialists ➢ To enhance the performance of average worker to the level of an expert Limitations of expert system ➢ Expensive computer program ➢ Mostly developed not in regional languages ➢ Requires AC power and internet connection all the time ➢ Complex software requires computer skilled personnel Modules of expert system in agriculture ➢ COMAX: Integrated crop management in cotton ➢ SOYEX: Soybean oil extraction expert system ➢ PLANT/ds: Diagnosis of soybean diseases ➢ MAIZE: Maize expert system for field crop management ➢ SEMAGI: Weed control decision making in sunflowers ➢ Rice Crop Doctor: Developed by National Institute of Agricultural Extension Management (MANAGE) Difference between conventional and expert system of extension Conventional Extension ➢ Universal approachability of same information is a problem ➢ Information is given whatever is available without considering needs and resources ➢ No Cost benefit analysis ➢ Information flow depends on availability of agent ➢ Require users to draw their own conclusion from facts Expert System of Extension ➢ Universal approachability of same information is possible ➢ Information is chosen based on their needs and resources ➢ Cost benefit analysis ➢ Information through Cyber Cafe at any place at any time ➢ Conclusion is drawn based on the decision given by the expert

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