Introduction To RDBMS & SQL Server 11
- What are Databases & RDBMSLecture1.1
- Create data model (Schema –Meta Data –ER Diagram) & databaseLecture1.2
- Data Integrity Constraints & types of RelationshipsLecture1.3
- Introduction to SQL Server & SQLLecture1.4
- Working with TablesLecture1.5
- SQL Management Studio & Utilizing the Object ExplorerLecture1.6
- Basic concepts – Queries, Data types & NULL Values, Operators, Comments in SQL, Joins, Indexes, Functions, Views, Sorting, filtering, sub querying, summarising, merging, appending, new variable creation, case when statement usage etc.Lecture1.7
- Data manipulation – Reading & Manipulating a Single and multiple tablesLecture1.8
- Data based objects creation(DDL Commands) (Tables, Indexes, views etc)Lecture1.9
- Optimizing your workLecture1.10
- End to End to data manipulation exerciseLecture1.11
Hadoop(Big Data) Eco-System 12
- Motivation for HadoopLecture2.1
- Limitations and Solutions of existing Data Analytics ArchitectureLecture2.2
- Comparison of traditional data management systems with Big Data Evaluate key framework requirements for Big Data analyticsLecture2.3
- Hadoop Ecosystem & core componentsLecture2.4
- The Hadoop Distributed File System – Concept of data storageLecture2.5
- Explain different types of cluster setups(Fully distributed/Pseudo etc.)Lecture2.6
- Hadoop Cluster Overview & ArchitectureLecture2.7
- A Typical enterprise cluster – Hadoop Cluster ModesLecture2.8
- HDFS Overview & Data storage in HDFSLecture2.9
- Get the data into Hadoop from local machine(Data Loading ) – vice versaLecture2.10
- Practice complete data loading and managing them using command line(Hadoop commands) & HUELecture2.11
- Map Reduce Overview (Traditional way Vs. MapReduce way)Lecture2.12
RDBMS & Hadoop Integration Using Sqoop 3
Data Analysis Using Hive 14
- Apache Hive – Hive Vs. PIG – Hive Use CasesLecture4.1
- Discuss the Hive data storage principleLecture4.2
- Explain the File formats and Records formats supported by the Hive environmentLecture4.3
- Perform operations with data in HiveLecture4.4
- Hive QL: Joining Tables, Dynamic Partitioning, Custom Map/Reduce ScriptsLecture4.5
- Hive Script, Hive UDFLecture4.6
- Join datasets using a variety of techniques, including Map-side joins and Sort-Merge-Bucket joinsLecture4.7
- Use advanced Hive features like windowing, views and ORC filesLecture4.8
- Hive Persistence formatsLecture4.9
- Loading data in Hive – MethodsLecture4.10
- Serialization & DeserializationLecture4.11
- Integrating external BI tools with Hadoop HiveLecture4.12
- Use Hive to compute ngrams on Avro-formatted filesLecture4.13
- Use the Hive analytics functions (rank, dense_rank, cume_dist, row_number)Lecture4.14
Data Analysis Using Impala 2
- Impala & ArchitectureLecture5.1
- How Impala executes Queries and its importanceLecture5.2
Data Transformation And Analysis Using Pig 10
- Introduction to Data Analysis ToolsLecture6.1
- Apache PIG – MapReduce Vs Pig, Pig Use CasesLecture6.2
- PIG’s Data ModelLecture6.3
- PIG StreamingLecture6.4
- Pig Latin Program & ExecutionLecture6.5
- Pig Latin : Relational Operators, File Loaders, Group Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDFLecture6.6
- PIG MacrosLecture6.7
- Parameterization in Pig (Parameter Substitution)Lecture6.8
- Use Pig to automate the design and implementation of MapReduce applicationsLecture6.9
- Use Pig to apply structure to unstructured Big DataLecture6.10
SPARK: Introduction 7
- Introduction to Apache SparkLecture7.1
- Streaming Data Vs. In Memory DataLecture7.2
- Map Reduce Vs. SparkLecture7.3
- Modes of SparkLecture7.4
- Spark Installation DemoLecture7.5
- Overview of Spark on a clusterLecture7.6
- Spark Standalone ClusterLecture7.7
Spark: Spark In Practice 7
- Invoking Spark ShellLecture8.1
- Creating the Spark ContextLecture8.2
- Loading a File in ShellLecture8.3
- Performing Some Basic Operations on Files in Spark ShellLecture8.4
- Caching OverviewLecture8.5
- Distributed PersistenceLecture8.6
- Spark Streaming OverviewLecture8.7
Introduction To Scala For Apache Spark 2
Resilient Distributed DataSets (RDD) 5
- Understanding & Loading data into RDDLecture10.1
- Hadoop RDD, Filtered RDD, Joined RDDLecture10.2
- Transformations, Actions and Shared VariablesLecture10.3
- Spark Operations on YARNLecture10.4
- Sequence File ProcessingLecture10.5
Spark SQL: Analysing Structured Data 4
- Spark Structured Query LanguageLecture11.1
- Linking with Spark SQLLecture11.2
- Initializing Spark SQL and execute Basic QueriesLecture11.3
- Analyze Hive and Spark SQL ArchitectureLecture11.4
Spark Streaming (Introduction) 3
Spark MLLib: Scaleable Machine Learning On Spark (Introduction) 3
- Introduction to MLibLecture13.1
- Examples for usage of Spark MLLibLecture13.2
- Data Types and working with vectorsLecture13.3
Introduction To NoSQL 9
- Limitations of RDBMS & Motivation for NoSQLLecture14.1
- Nosql Design goals & AdvantagesLecture14.2
- Types of Nosql databases (Categories) – Cassandra/MongoDB/HbaseLecture14.3
- CAP theoremLecture14.4
- NoSQL database queries and update languagesLecture14.5
- Indexing and searching in NoSQL DatabasesLecture14.6
- Reducing data via reduce functionLecture14.7
- Clustering and scaling of NoSQL DatabaseLecture14.8
- Query behaviors in MongoDBLecture14.9
MongoDB Architecture & Installation 9
- Overview & Architecture of MongoDBLecture15.1
- Depth understanding of Database and CollectionLecture15.2
- Documents and Key/Values etc.Lecture15.3
- Introduction to JSON and BSON DocumentsLecture15.4
- Installing MongoDB on LinuxLecture15.5
- Usage of various MongoDB Tools available with MongoDB packageLecture15.6
- Introduction to MongoDB shellLecture15.7
- MongoDB Data typesLecture15.8
- CRUD concepts & operationsLecture15.9
Data Modeling & Schema Design - MongoDB 7
- Data modeling concepts & approachLecture16.1
- Analogy between RDBMS & MongoDB data modelingLecture16.2
- Model relationship between documents (one-one, one-many)Lecture16.3
- Challenges in modelingLecture16.4
- Model tree structures with parent references and with child referencesLecture16.5
- Query buildingLecture16.6
- Model data for Atomic operations and support searchLecture16.7
MongoDB Drivers (Node.JS) 3
- API and drivers for MongoDB, HTTP and REST interface,Lecture17.1
- Install Node.js, dependenciesLecture17.2
- Node.js find & display data, Node.js saving and deleting dataLecture17.3
MongoDB - Indexing 1
MongoDB Administration, Scale & Security 6
- MongoDB monitoring, health check, backups & Recovery options, Performance TuningLecture19.1
- Data Imports & Exports to & from MongoDBLecture19.2
- Introduction to Scalability & AvailabilityLecture19.3
- MongoDB replication, Concepts around sharding, Types of sharding and Managing shardsLecture19.4
- Master – Slave ReplicationLecture19.5
- Security concepts & Securing MongoDBLecture19.6
MongoDB – Application Development 1
- Creation of MongoDB appLecture20.1
Introduction To Cloud Computing 8
- What is Cloud Computing? Why it matters?Lecture21.1
- Cloud Companies (Microsoft Azure, GCP, AWS ) & their Cloud Services (Compute, storage, networking, apps, cognitive etc.)Lecture21.2
- Traditional IT Infrastructure vs. Cloud InfrastructureLecture21.3
- Use Cases of Cloud computingLecture21.4
- Overview of Cloud Segments: IaaS, PaaS, SaaSLecture21.5
- Overview of Cloud Deployment ModelsLecture21.6
- Overview of Cloud SecurityLecture21.7
- Introduction to AWS, Microsoft Azure Cloud and OpenStack. Similarities and differences between these Public / Private Cloud offeringsLecture21.8
Big Data Analytics Using Cloud Computing (GCP Or Azure Or AWS) 11
- Creating Virtual machineLecture22.1
- Overview of available Big Data products & AnalyticsLecture22.2
- Services in CloudLecture22.3
- Storage servicesLecture22.4
- Database ServicesLecture22.5
- Compute ServicesLecture22.6
- Analytics ServicesLecture22.7
- Machine Learning ServicesLecture22.8
- Manage Hadoop Ecosystem & Spark, NOSQL in the Cloud ServicesLecture22.9
- Creating Data pipelinesLecture22.10
- Scaling Data Analysis & Machine Learning ModelsLecture22.11
Case Studies 7
- Data Storage Using HDFSLecture23.1
- Processing Data Using Map ReduceLecture23.2
- Data Analysis Using PigLecture23.3
- Data Integration Using Sqoop & FlumeLecture23.4
- Data Analysis Using HiveLecture23.5
- Hbase-NoSql Data Base CreationLecture23.6
- Final Project : Integration Of Hadoop ComponentsLecture23.7
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