Database and Big Data Collection

The New Horizons Database & Big Data Collection offers a vast array of learning options with instant access to thousands of learning assets across a wide choice of modalities (videos, courses, books, assessments, mentoring, etc.). These learning assets can be used to support database & big data professionals’ continuous learning needs from solving an immediate technical problem, to buildinga well-rounded set of skills and preparing for certification exams.

This is an Online ANYTIME course library and includes multiple individual online courses. Online ANYTIME gives you access to a self-paced training solution that uses the same core course content as our world-renowned Instructor-Led Training.

Database and Big Data Collection COURSE LIST

  • A/B Testing, Bayesian Networks, and Support Vector Machine
  • Accessing Data with Spark: An Introduction to Spark
  • Accessing Data with Spark: Data Analysis using Spark SQL
  • Accessing Data with Spark: Data Analysis Using the Spark DataFrame API
  • Administering a SQL Database Infrastructure Expert Live with Encore
  • Administering Microsoft SQL Server 2012 Databases Expert Live with Encore
  • Advanced TIBCO Spotfire
  • Aggregating Data in SQL Server 2016
  • An Overview of Apache Cassandra
  • Analytics by Function
  • Apache Hadoop
  • Apache Hadoop on Amazon EMR
  • Apache HBase Fundamentals: Access Data through the Shell and Client API
  • Apache HBase Fundamentals: Advanced API, Administration, and MapReduce
  • Apache HBase Fundamentals: Installation, Architecture, and Data Modeling
  • Apache Kafka Development
  • Apache Kafka Operations
  • Apache Solr - Query and Data Management
  • Apache Solr – Deployment and Configuration
  • Apache Spark SQL
  • Apache Storm Introduction - API and Topology
  • Apache Storm Introduction – Architecture and Installation
  • Applied Predictive Modeling
  • Auditing, Logging, and Event Handling
  • Automation and Machine Learning
  • Automation Design & Robotics
  • Azure SQL Database Encryption
  • Azure Virtual Machines
  • Backing Up, Recovering, Importing, and Exporting Data in Oracle Database 12c
  • Balancing the Four Vs of Data: The Four Vs of Data
  • Base SAS 9 Programming: Creating Reports
  • Base SAS 9 Programming: Data Structures
  • Base SAS 9 Programming: Inputs and Outputs
  • Base SAS 9 Programming: Introduction to Data Sets
  • Base SAS 9 Programming: The SAS Environment
  • Base SAS 9 Programming: Working with Data Sets
  • Batch Solutions with Hive and Apache Pig
  • Bayesian Methods: Advanced Bayesian Computation Model
  • Bayesian Methods: Bayesian Concepts & Core Components
  • Bayesian Methods: Implementing Bayesian Model and Computation with PyMC
  • BI with QlikView: Application Deployment and Performance
  • BI with QlikView: Dashboards and Comparative Analysis
  • BI with QlikView: Data Governance and Metadata Management
  • BI with QlikView: Data Modeling
  • BI with QlikView: Getting Started
  • BI with QlikView: Macros and Properties
  • BI with QlikView: Scripting and Designing
  • BI with QlikView: Server
  • Big Data - The Legal Perspective
  • Big Data Corporate Leadership Perspective
  • Big Data Engineering Perspectives
  • Big Data Fundamentals
  • Big Data Interpretation
  • Big Data Marketing Perspective
  • Big Data Opportunities and Challenges
  • Big Data Sales Perspective
  • Big Data Strategic Planning
  • Bitcoin Internals and Wallet Configuration
  • Bitcoin Technology Fundamentals
  • Blockchain and Your Business
  • Blockchain Architectural Components and Platforms
  • Blockchain in Action and IoT
  • Blockchain Trust and Design
  • Blockchains & Ethereum: Introduction
  • Blockchains & Ethereum: Mining and Smart Contracts in Ethereum
  • Blockchains & Ethereum: Performing Transactions in Ethereum
  • Building Data Pipelines
  • Building Decentralized Applications for Ethereum: An Introduction to dApps
  • Building Decentralized Applications for Ethereum: Bespoke Ethereum Tokens
  • Building Decentralized Applications for Ethereum: Building the Back End
  • Building Decentralized Applications for Ethereum: Building the Front End
  • Building ML Training Sets: Introduction
  • Building ML Training Sets: Preprocessing Datasets for Classification
  • Building ML Training Sets: Preprocessing Datasets for Linear Regression
  • Building Solutions using Kafka and HBase
  • Capacity Management for Hadoop Clusters
  • Cassandra vs. SQL
  • Cloud Blockchains: An Introduction to Blockchain on the Cloud
  • Cloud Blockchains: Building Apps on the Azure Blockchain Workbench
  • Cloud Blockchains: Multi-Organization Networks on Amazon Managed Blockchain
  • Cloud Blockchains: Single Organization Networks on Amazon Managed Blockchain
  • Cloud Data Science: Azure AI Gallery and Azure Machine Learning
  • Cloud Data Science: Consume Models and APIs Using Azure Machine Learning Studio
  • Cloud Data Science: Data Cleanup with Azure Machine Learning Studio
  • Cloud Data Science: Deploying Models with Azure Machine Learning Studio
  • Cloud Data Science: Importing and Exporting in Azure Machine Learning Studio
  • Cloud Data Science: Introduction to Azure Machine Learning
  • Cloud Data Science: Microsoft Cognitive Toolkit and Azure Machine Learning
  • Cloud Data Science: Optimize and Validate Models in Azure Machine Learning Studio
  • Cloud Data Science: SQL Server & Azure Machine Learning
  • Cloud Data Science: Summarize Data with Azure Machine Learning Studio
  • Cloud Data Science: Transforming Data in Azure Machine Learning Studio
  • Cloud Data Science: Using Algorithms in Azure Machine Learning Studio
  • Cloud Data Science: Virtual Machines & HDInsight
  • Cloudera Manager and Hadoop Clusters
  • Cluster Analysis and Ensemble Learning
  • Clustering Techniques
  • Clustering with Kafka
  • Columnstore Indexes
  • Complex Visualizations and Analytics
  • Compliance Issues and Strategies: Data Compliance
  • Components of a SQL Server 2016 Installation
  • Connection Managers and Data Sources
  • Connectivity and Space Management in Oracle Database 12c
  • Correlation & Regression
  • Create Spark Streaming Applications
  • Creating Data APIs Using Node.js
  • Data Access & Governance Policies: Data Access Oversight and IAM
  • Data Access & Governance Policies: Data Classification, Encryption, and Monitoring
  • Data Analysis Application
  • Data Analysis Concepts
  • Data Analysis Using Spark SQL and Hive
  • Data Analytics using Power BI: Concepts
  • Data Analytics Using Power BI: Data Modeling and Visualization
  • Data Analytics Using Power BI: Data Sourcing and Preparation
  • Data and Analytics Technologies at Work
  • Data Architecture - Deep Dive: Design & Implementation
  • Data Architecture - Deep Dive: Microservices & Serverless Computing
  • Data Architecture Primer
  • Data Classification and Machine Learning
  • Data Collection & Exploration
  • Data Communication and Visualization
  • Data Engineering Fundamentals
  • Data Exploration
  • Data Factory with Hive
  • Data Factory with Oozie and Hue
  • Data Factory with Pig
  • Data Filtering
  • Data Flow for the Hadoop Ecosystem
  • Data Flow Implementation
  • Data Gathering
  • Data Integration
  • Data Lake: Architectures & Data Management Principles
  • Data Lake: Framework & Design Implementation
  • Data Load Options
  • Data Mining, Data Distributions, & Hypothesis Testing
  • Data Preprocessing
  • Data Quality Projects
  • Data Quality Services (DQS) and Master Data Services (MDS)
  • Data Reduction & Exploratory Data Analysis (EDA)
  • Data Refinery with YARN and MapReduce
  • Data Repository with Flume
  • Data Repository with HDFS and HBase
  • Data Repository with Sqoop
  • Data Rollbacks: Transaction Management & Rollbacks in NoSQL
  • Data Rollbacks: Transaction Rollbacks & Their Impact
  • Data Science 10: Data Research Exploration Techniques
  • Data Science 2: Data Driven Organizations
  • Data Science 9: Data Research Techniques
  • Data Science Overview
  • Data Science Statistics: Applied Inferential Statistics
  • Data Science Statistics: Common Approaches to Sampling Data
  • Data Science Statistics: Inferential Statistics
  • Data Science Statistics: Simple Descriptive Statistics
  • Data Science Statistics: Using Python to Compute & Visualize Statistics
  • Data Scientist 14: Data Research Statistical Approaches
  • Data Silos, Lakes, & Streams: Introduction
  • Data Silos, Lakes, & Streams: Sources, Visualizations, & ETL Operations
  • Data Silos, Lakes, and Streams: Data Lakes on AWS
  • Data Sources: Implementing Edge on the Cloud
  • Data Sources: Integration
  • Data Tools: Machine Learning & Deep Learning in the Cloud
  • Data Tools: Technology Landscape & Tools for Data Management
  • Data Transformation
  • Data Visualization and Predictive Analytics
  • Data Visualization: Essentials
  • Data Warehouse Essential: Architecure Frameworks and Implementation
  • Data Warehouse Essential: Concepts
  • Data Warehousing with Azure: Analytics and Reporting
  • Data Warehousing with Azure: Architecture & Modeling Techniques
  • Data Warehousing with Azure: Data Lake Implementation Using Azure
  • Data Warehousing with Azure: Implementing Azure SQL Data Warehouse
  • Data Warehousing with Azure: Managing Azure Data Lake
  • Data Warehousing with Azure: Working with SQL Data Warehouse Objects
  • Data Warehousing with Hadoop: HDInsight and Retail Sales Implementation Using Hive
  • Data Warehousing with Hadoop: Managing Big Data Using HDInsight Hadoop
  • Data Warehousing with Hadoop: Microsoft Analytics Platform System and Hive
  • Data Warehousing with Hadoop: Spark, HDInsight and Cluster Management
  • Data Wrangler 4: Cleaning Data in R
  • Data Wrangling in R
  • Data Wrangling with Pandas: Advanced Features
  • Data Wrangling with Pandas: Visualizations and Time-Series Data
  • Data Wrangling with Pandas: Working with Series & DataFrames
  • Database Instances
  • Database Maintenance and Performance Tuning in Oracle Database 12c
  • Database Programmability Objects and Non-Relational Data
  • Database Systems and Relational Databases
  • Debugging in R
  • Decision Tree and Classification Analysis
  • Deep Learning with Keras
  • Deploying Applications to Microsoft Azure SQL Databases
  • Deploying Data Tools: Data Science Tools
  • Deploying Hadoop Clusters
  • Design Thinking for Innovation: Brainstorming and Ideation
  • Design Thinking for Innovation: Defining Opportunities
  • Design Thinking for Innovation: Prototyping and Testing
  • Design Thinking for Innovation: Stakeholder Engagement
  • Designing a Fact Table
  • Designing and Implementing Dimensions
  • Designing Batch Processing and Data Security
  • Designing Control Flow
  • Designing Data Flow
  • Designing Hadoop Clusters
  • Designing the Lambda Architecture and Real-time Processing
  • Develop Real-time Processing Solutions with Apache Storm
  • Developing SQL Databases Expert Live with Encore
  • Developing with Blockchain
  • DevOps for Data Scientists: Containers for Data Science
  • DevOps for Data Scientists: Data DevOps Concepts
  • DevOps for Data Scientists: Data Science DevOps
  • DevOps for Data Scientists: Deploying Data DevOps
  • Diving into the World of Spotfire
  • Domain-Specific Tools in R
  • Ecosystem for Hadoop
  • Encore Session 1: Encryption, Data Access, Permissions, and Auditing
  • Encore Session 1: Installing SQL Server Instances and Creating Databases
  • Encore Session 1: SQL Server 2016 Database Objects, Indexes, and Views
  • Encore Session 2: Backing Up and Restoring Databases
  • Encore Session 2: Columnstore Indexes and Programmability Objects
  • Encore Session 2: Manage Data in SQL 2012
  • Encore Session 3: Managing Database Integrity
  • Encore Session 3: Optimizing and Troubleshooting SQL 2012
  • Encore Session 3: Triggers, Functions, Transactions, and Isolation Levels
  • Encore Session 4: Managing Database Concurrency
  • Encore Session 4: Monitoring Database Activity, Queries, and SQL Server Instances
  • Encore Session 4: Recovering Databases, Configuring Mail, and Automating Tasks
  • Encore Session 5: Implementing Security
  • Encore Session 5: Managing Indexes and Statistics
  • Encore Session 5: Optimize SQL Database Objects and Infrastructure
  • Encore Session 6: Database Instances and Performance Tuning
  • Encore Session 6: High Availability
  • Encore Session 6: High Availability and Disaster Recovery
  • Exploring Blockchain
  • Filter and Modify Data in SQL Server 2016
  • Framing Opportunities for Effective Data-driven Decision Making
  • Fundamental Methods for Data Science in R
  • GCP DevOps: CloudOps with Google Cloud Platform
  • Generic Database Fundamentals: Architecture and Normalization Concepts
  • Generic Database Fundamentals: Relation Algebra, SQL, and Concurrency Concepts
  • Generic Design and Modeling Databases: Concepts and Conceptual Design
  • Generic Design and Modeling Databases: Logical and Physical Design
  • Getting Started with Hadoop: Advanced Operations Using MapReduce
  • Getting Started with Hadoop: Developing a Basic MapReduce Application
  • Getting Started with Hadoop: Filtering Data Using MapReduce
  • Getting Started with Hadoop: Fundamentals & MapReduce
  • Getting Started with Hadoop: MapReduce Applications With Combiners
  • Getting Started with Hive: Bucketing & Window Functions
  • Getting Started with Hive: Introduction
  • Getting Started with Hive: Loading and Querying Data
  • Getting Started with Hive: Optimizing Query Executions
  • Getting Started with Hive: Optimizing Query Executions with Partitioning
  • Getting Started with Hive: Viewing and Querying Complex Data
  • Getting Started with Microsoft Azure HDInsight and Administering clusters
  • Getting Started with Microsoft R
  • Getting Started with the Software and Integrating Data
  • Guiding the Analysis for Effective Data-driven Decision Making
  • Hadoop Cluster Availability
  • Hadoop Clusters
  • Hadoop Distributed File System
  • Hadoop HDFS: File Permissions
  • Hadoop HDFS: Introduction
  • Hadoop HDFS: Introduction to the Shell
  • Hadoop HDFS: Working with Files
  • Hadoop in the Cloud
  • Hadoop Maintenance and Distributions
  • Hadoop Ranger
  • Hands-On Labs
  • IBM BigInsights Fundamentals: Analyzing, Querying, and Extracting Big Data
  • IBM BigInsights Fundamentals: Hadoop Solution
  • Implementing Control Flow
  • Implementing Governance Strategies
  • Implementing Smart Contracts Using Ethereum
  • Importing and Manipulating Data
  • In Depth with NoSQL
  • Indexers, Clusters, and Advanced Search
  • Ingesting Data and Computing for Batch Processing
  • Ingesting Data and Computing for Real-time Processing
  • Installation of Hadoop
  • Installing and Upgrading SQL Server 2016
  • Interactive Processing using Apache Phoenix on HBase
  • Interactive Queries with Spark SQL and Interactive Hive
  • Introduction to Apache Spark
  • Introduction to Data Modeling in Hadoop
  • Introduction to Designing a Relational Database
  • Introduction to Digital Currency
  • Introduction to Hadoop
  • Introduction to SQL
  • Introduction to SQL: Managing Table Design
  • Introduction to SQL: Multiple Tables and Advanced Queries
  • Introduction to SQL: Views, Transactions, and SQL Security Architecture
  • Java ASYNC Interface
  • K-Nearest Neighbor (k-NN) & Artificial Neural Networks
  • Kafka Integration with Spark
  • Kafka Integration with Storm
  • Kafka Real-time Applications
  • Key Statistical Concepts
  • Linear and Logistic Regression
  • Linear Regression Models: An Introduction to Logistic Regression
  • Linear Regression Models: Building Simple Regression Models with Scikit Learn and Keras
  • Linear Regression Models: Introduction to Linear Regression
  • Linear Regression Models: Multiple and Parsimonious Linear Regression
  • Linear Regression Models: Simplifying Regression and Classification with Estimators
  • Live Session 1: Encryption, Data Access, Permissions, and Auditing
  • Live Session 1: Installing SQL Server Instances and Creating Databases
  • Live Session 1: SQL Server 2016 Database Objects, Indexes, and Views
  • Live Session 2: Backing Up and Restoring Databases
  • Live Session 2: Columnstore Indexes and Programmability Objects
  • Live Session 2: Manage Data in SQL 2012
  • Live Session 3: Managing Database Integrity
  • Live Session 3: Optimizing and Troubleshooting SQL 2012
  • Live Session 3: Triggers, Functions, Transactions, and Isolation Levels
  • Live Session 4: Managing Database Concurrency
  • Live Session 4: Monitoring Database Activity, Queries, and SQL Server Instances
  • Live Session 4: Recovering Databases, Configuring Mail, and Automating Tasks
  • Live Session 5: Implementing Security
  • Live Session 5: Managing Indexes and Statistics
  • Live Session 5: Optimize SQL Database Objects and Infrastructure
  • Live Session 6: Database Instances and Performance Tuning
  • Live Session 6: High Availability
  • Live Session 6: High Availability and Disaster Recovery
  • Machine Learning Examples for Data Science in R
  • Machine Learning, Propensity Score, & Segmentation Modeling
  • Management of Relational Database Data
  • Managing Activities and Data for Azure Big Data Analytics
  • Managing an Oracle Database 12c Instance
  • Managing Big Data Operations
  • Managing Database Concurrency
  • Managing HDInsight Data, Jobs, and Security
  • MapReduce Essentials
  • Math for Data Science & Machine Learning
  • Microsoft Azure SQL Database Security
  • Microsoft SQL Server 2012 – Developing Databases: CLR Integration
  • Microsoft SQL Server 2012 – Developing Databases: Implementing Indexes
  • Microsoft SQL Server 2012 – Developing Databases: Implementing Tables and Views
  • Microsoft SQL Server 2012 – Developing Databases: Managing and Troubleshooting
  • Microsoft SQL Server 2012 – Developing Databases: Stored Procedures
  • Microsoft SQL Server 2012 – Developing Databases: Tuning and Optimizing Queries
  • Microsoft SQL Server 2012 – Developing Databases: Working with Data
  • Microsoft SQL Server 2012 – Developing Databases: Working with XML Data
  • Microsoft SQL Server 2012 – Implementing a Data Warehouse: Design and Deployment
  • Microsoft SQL Server 2012 – Implementing a Data Warehouse: ETL Solutions
  • Microsoft SQL Server 2012: Configuring High Availability
  • Microsoft SQL Server 2012: Creating Database Objects
  • Microsoft SQL Server 2012: Creating Functions and Triggers
  • Microsoft SQL Server 2012: Creating Programming Objects and Optimizing Queries
  • Microsoft SQL Server 2012: Instance Configuration and Database Creation
  • Microsoft SQL Server 2012: Managing Database Data
  • Microsoft SQL Server 2012: Managing Databases and Automating Tasks
  • Microsoft SQL Server 2012: Managing XML Data
  • Microsoft SQL Server 2012: Manipulate Data Using Operators and Functions
  • Microsoft SQL Server 2012: Querying Basics and Modifying Data
  • Microsoft SQL Server 2014 - Designing BI Solutions: Availability and Recovery
  • Microsoft SQL Server 2014 - Designing BI Solutions: BI Infrastructure Design
  • Microsoft SQL Server 2014 - Designing BI Solutions: Data Models
  • Microsoft SQL Server 2014 - Designing BI Solutions: Extract, Transform, and Load
  • Microsoft SQL Server 2014 - Designing BI Solutions: MDX Queries and Performance
  • Microsoft SQL Server 2014 - Designing BI Solutions: Reporting Services
  • Microsoft SQL Server 2014 - Designing BI Solutions: SharePoint Integration
  • Microsoft SQL Server 2014 - Designing Solutions: Backup and Recovery
  • Microsoft SQL Server 2014 - Designing Solutions: Clustering and AlwaysOn
  • Microsoft SQL Server 2014 - Designing Solutions: High Availability
  • Microsoft SQL Server 2014 - Designing Solutions: Planning Infrastructure
  • Microsoft SQL Server 2014 - Designing Solutions: Private Clouds
  • Microsoft SQL Server 2014 - Designing Solutions: Windows Azure SQL Database
  • Microsoft SQL Server 2014 - Developing Databases: New Features
  • Microsoft SQL Server 2014: Create and Manage Tabular Data Models
  • Microsoft SQL Server 2014: Design and Implement Dimensions
  • Microsoft SQL Server 2014: Design and Install Analysis Services and Tools
  • Microsoft SQL Server 2014: Design Reports and Create Data Sources and Datasets
  • Microsoft SQL Server 2014: Designing Multidimensional Models and Data Sources
  • Microsoft SQL Server 2014: Manage Reporting Services
  • Microsoft SQL Server 2014: Manage, Maintain, and Troubleshoot SSAS
  • Microsoft SQL Server 2014: MDX Queries, Process Models, and Deploy Databases
  • Microsoft SQL Server 2014: Process Report and Create Subscriptions and Schedules
  • Microsoft SQL Server 2014: Report Formatting and Interactivity
  • Microsoft SQL Server 2016 First Look: Preview
  • Microsoft SQL Server 2016: Auditing
  • Microsoft SQL Server 2016: Backing Up Databases
  • Microsoft SQL Server 2016: Data Access and Permissions
  • Microsoft SQL Server 2016: Encryption
  • Microsoft SQL Server 2016: High Availability and Disaster Recovery
  • Microsoft SQL Server 2016: Managing Database Integrity
  • Microsoft SQL Server 2016: Managing Indexes and Statistics
  • Microsoft SQL Server 2016: Monitoring Database Activity and Queries
  • Microsoft SQL Server 2016: Monitoring SQL Server Instances
  • Microsoft SQL Server 2016: Restoring Databases
  • Microsoft SQL Server Data Warehousing and Business Intelligence Overview
  • Microsoft SQL Server: Implement and Configure Cubes
  • Microsoft SQL Server: Implement Partitions and Custom Logic
  • Migrating Client Applications
  • Model Development, Validation, & Evaluation
  • Model Life Cycle Management
  • Modifying and Summarizing Data
  • MongoDB for Data Wrangling: Aggregation
  • MongoDB for Data Wrangling: Querying
  • MongoDB: Backups, Monitoring, and Stats
  • MongoDB: Cloud and Hadoop Deployments
  • MongoDB: Indexes and Query Optimization
  • MongoDB: Installation Overview
  • MongoDB: Integration with Python
  • MongoDB: Integration with Spark
  • MongoDB: Java REST and GridFS
  • MongoDB: Map Reduce, Atomic Counters, and Binary Data
  • MongoDB: Replication and Security
  • MongoDB: System Management
  • MongoDB: User Management
  • MongoDB: Write, Read, and Aggregate Data
  • More Spotfire Visualization Techniques
  • Motivating Action with a Compelling and Data-driven Story
  • MySQL Database Development: Database Design Fundamentals
  • MySQL Database Development: DDL Statements
  • MySQL Database Development: GIS, Cloud, and Connectors for MySQL
  • MySQL Database Development: Introduction
  • MySQL Database Development: Manipulating Data
  • MySQL Database Development: Query and Performance Optimization
  • MySQL Database Development: SELECT Statement and Operators
  • MySQL Database Development: Stored Routines, Triggers, and the InnoDB memcached Plugin
  • MySQL Database Development: Working with Functions
  • MySQL: Administration, Transactions, Optimization, Scaling, Backup, and Recovery
  • MySQL: Advanced Routines, Optimization, and DCL
  • MySQL: Creating & Updating Tables
  • MySQL: Database Concepts, Design, and Installation
  • MySQL: General Syntax, Advanced Queries, and Stored Programs
  • MySQL: Getting Started
  • MySQL: Grouping & Aggregation Operations
  • MySQL: Performance Monitoring, Database Health and Integrity, and Security
  • MySQL: Querying Data
  • MySQL: Querying Data Using the SELECT Statement
  • MySQL: Storage Engines, Advanced Indexing, and Maintenance
  • MySQL: Transactions, Savepoints, & Locks
  • MySQL: Triggers & Stored Procedures
  • MySQL: Understanding & Implementing Joins
  • MySQL: Using the Data Manipulation and Definition Statements
  • MySQL: Views, Indices, & Normal Forms
  • NoSQL Concepts and Background
  • NoSQL for FSD Development
  • NoSQL Models and Applications
  • Operating Hadoop Clusters
  • Operationalize and Design with Spark
  • Operators and Expressions in SQL Server 2016
  • Optimize SQL Database Objects and Infrastructure
  • Optimizing the Customer Experience
  • Oracle 12c Performance Tuning: Application Monitoring and SQL Diagnostics
  • Oracle 12c Performance Tuning: Automatic Workload Repository
  • Oracle 12c Performance Tuning: Introduction
  • Oracle 12c Performance Tuning: Measuring and Maintaining SQL Performance
  • Oracle 12c Performance Tuning: Metrics and Monitoring
  • Oracle 12c Performance Tuning: Performance Tuning Summary
  • Oracle 12c Performance Tuning: Tuning Instance Memory
  • Oracle 12c Performance Tuning: Tuning Problem SQL Statements
  • Oracle Database 11g Release 2: Application Performance Enhancements
  • Oracle Database 11g Release 2: ASM, Storage and Partitioning Enhancements
  • Oracle Database 11g Release 2: Backup and Recovery
  • Oracle Database 11g Release 2: Backup, Recover, Archive, and Repair Data
  • Oracle Database 11g Release 2: Database Architecture and Installation
  • Oracle Database 11g Release 2: Database Architecture and Recovery Operations
  • Oracle Database 11g Release 2: Database Creation and Instance Management
  • Oracle Database 11g Release 2: Database Diagnostics and Flashback Technologies
  • Oracle Database 11g Release 2: Diagnosability Enhancements
  • Oracle Database 11g Release 2: Installation and Oracle Restart
  • Oracle Database 11g Release 2: Intelligent Infrastructure Enhancements
  • Oracle Database 11g Release 2: Managing Concurrency, Undo, and Auditing
  • Oracle Database 11g Release 2: Managing Database Maintenance and Performance
  • Oracle Database 11g Release 2: Managing Database Memory and Performance
  • Oracle Database 11g Release 2: Managing Database Resources and the Scheduler
  • Oracle Database 11g Release 2: Managing Database Space and Duplication
  • Oracle Database 11g Release 2: Moving Data and Oracle Support
  • Oracle Database 11g Release 2: Oracle Partitioning and Security Features
  • Oracle Database 11g Release 2: Oracle Scheduler and Secure Backup
  • Oracle Database 11g Release 2: Performing Restore and Recovery Tasks
  • Oracle Database 11g Release 2: SQL Monitoring and Performance Enhancements
  • Oracle Database 11g Release 2: Storage Structures and User Security
  • Oracle Database 11g Release 2: The ASM Instance and Network Connectivity
  • Oracle Database 11g Release 2: The RMAN Catalog and Creating Backups
  • Oracle Database 11g Release 2: Using Change Management Solutions
  • Oracle Database 11g Release 2: Using, Monitoring and Tuning RMAN
  • Oracle Database 11g: Configure, Manage, and Use Services in RAC
  • Oracle Database 11g: Installation of Clusterware and RAC
  • Oracle Database 12c - Backup and Recovery: Configuring for Recoverability
  • Oracle Database 12c - Backup and Recovery: Duplicating Databases and Tuning RMAN
  • Oracle Database 12c - Backup and Recovery: Failure and Recovery Concepts
  • Oracle Database 12c - Backup and Recovery: Perform Recovery and Secure Backup
  • Oracle Database 12c - Backup and Recovery: Performing and Managing Backups
  • Oracle Database 12c - Backup and Recovery: Transporting Data and Performing PITR
  • Oracle Database 12c - Backup and Recovery: Using Flashback Technologies
  • Oracle Database 12c - Introduction to SQL: Data Conversion and Aggregating Data
  • Oracle Database 12c - Introduction to SQL: Data Manipulation Language
  • Oracle Database 12c - Introduction to SQL: Relational Database and SQL Developer
  • Oracle Database 12c - Introduction to SQL: Restrict, Sort, and Customize Output
  • Oracle Database 12c - Introduction to SQL: SQL*Plus and SELECT Statement
  • Oracle Database 12c - Introduction to SQL: Working with Joins and Subqueries
  • Oracle Database 12c - Introduction to SQL: Working with SET Operators and DDL
  • Oracle Database 12c – Install and Upgrade: Database Architecture
  • Oracle Database 12c – Install and Upgrade: Installation
  • Oracle Database 12c – Install and Upgrade: Upgrading
  • Oracle Database 12c R2 SQL: Controlling User Access
  • Oracle Database 12c R2 SQL: Conversion Functions and Conditional Expressions
  • Oracle Database 12c R2 SQL: Creating Other Schema Objects
  • Oracle Database 12c R2 SQL: Data Definition Language (DDL)
  • Oracle Database 12c R2 SQL: Data Manipulation Language and Transaction Control Language
  • Oracle Database 12c R2 SQL: Displaying Data from Multiple Tables
  • Oracle Database 12c R2 SQL: Managing Objects with Data Dictionary Views 
  • Oracle Database 12c R2 SQL: Managing Schema Objects    
  • Oracle Database 12c R2 SQL: Manipulating Data Using Advanced Queries
  • Oracle Database 12c R2 SQL: Reporting Aggregated Data Using the Group Functions   
  • Oracle Database 12c R2 SQL: Restricting and Sorting Data
  • Oracle Database 12c R2 SQL: SQL*Plus
  • Oracle Database 12c R2 SQL: Using Basic SELECT statements
  • Oracle Database 12c R2 SQL: Using Single-Row Functions to Customize Output   
  • Oracle Database 12c R2 SQL: Using Structured Query Language (SQL)
  • Oracle Database 12c R2 SQL: Using Subqueries to Solve Queries 
  • Oracle Database 12c R2 SQL: Using the Set Operators
  • Oracle Database 12c RAC Administration: Backup and Recovery
  • Oracle Database 12c RAC Administration: Client Connections and QoS
  • Oracle Database 12c RAC Administration: Day-to-Day Administration
  • Oracle Database 12c RAC Administration: Global Resource Management
  • Oracle Database 12c RAC Administration: Installing, Configuring, and Patching
  • Oracle Database 12c RAC Administration: Introduction to Oracle RAC
  • Oracle Database 12c RAC Administration: Monitoring and Tuning
  • Oracle Database 12c RAC Administration: Services and Multitenant Architecture
  • Oracle Database 12c: Enterprise Manager Cloud Control and Creating CDB and PDB
  • Oracle Database 12c: High Availability and Database Management
  • Oracle Database 12c: Managing CDB and PDB, and Data Optimization
  • Oracle Database 12c: Managing Security
  • Oracle Database 12c: Resource Manager, Online Operations, and ADR
  • Oracle Database 12c: Transporting Databases and Managing Data
  • Oracle Database 12c: Tuning SQL and Using ADDM
  • Oracle Database 12c: Using Automatic Data Optimization, Storage, and Archiving
  • Packages and Data Types
  • Performance Tuning
  • Performance Tuning of Hadoop Clusters
  • Planning AI Implementation
  • Positioning Powerful Messages to Enable Action
  • Post-Test 1: Encryption, Data Access, Permissions, and Auditing
  • Post-Test 1: Installing SQL Server Instances and Creating Databases
  • Post-Test 1: SQL Server 2016 Database Objects, Indexes, and Views
  • Post-Test 2: Backing Up and Restoring Databases
  • Post-Test 2: Columnstore Indexes and Programmability Objects
  • Post-Test 2: Manage Data in SQL 2012
  • Post-Test 3: Managing Database Integrity
  • Post-Test 3: Optimizing and Troubleshooting SQL 2012
  • Post-Test 3: Triggers, Functions, Transactions, and Isolation Levels
  • Post-Test 4: Managing Database Concurrency
  • Post-Test 4: Monitoring Database Activity, Queries, and SQL Server Instances
  • Post-Test 4: Recovering Databases, Configuring Mail, and Automating Tasks
  • Post-Test 5: Implementing Security
  • Post-Test 5: Managing Indexes and Statistics
  • Post-Test 5: Optimize SQL Database Objects and Infrastructure
  • Post-Test 6: Database Instances and Performance Tuning
  • Post-Test 6: High Availability
  • Post-Test 6: High Availability and Disaster Recovery
  • PostgreSQL Database Fundamentals Part #1
  • PostgreSQL Database Fundamentals Part #2
  • Powering Recommendation Engines: Recommendation Engines
  • Practice Exam: SQL 2012 Admin
  • Pre-Test 1: Encryption, Data Access, Permissions, and Auditing
  • Pre-Test 1: Installing SQL Server Instances and Creating Databases
  • Pre-Test 1: SQL Server 2016 Database Objects, Indexes, and Views
  • Pre-Test 2: Backing Up and Restoring Databases
  • Pre-Test 2: Columnstore Indexes and Programmability Objects
  • Pre-Test 2: Manage Data in SQL 2012
  • Pre-Test 3: Managing Database Integrity
  • Pre-Test 3: Optimizing and Troubleshooting SQL 2012
  • Pre-Test 3: Triggers, Functions, Transactions, and Isolation Levels
  • Pre-Test 4: Managing Database Concurrency
  • Pre-Test 4: Monitoring Database Activity, Queries, and SQL Server Instances
  • Pre-Test 4: Recovering Databases, Configuring Mail, and Automating Tasks
  • Pre-Test 5: Implementing Security
  • Pre-Test 5: Managing Indexes and Statistics
  • Pre-Test 5: Optimize SQL Database Objects and Infrastructure
  • Pre-Test 6: Database Instances and Performance Tuning
  • Pre-Test 6: High Availability
  • Pre-Test 6: High Availability and Disaster Recovery
  • Predictive Analytics & Big Data
  • Predictive Modelling Best Practices: Applying Predictive Analytics
  • Preparing Impactful Presentations that Drive Decision Makers to Action
  • Process & Application
  • Programmability Objects
  • Programming Techniques in R
  • Programming with NoSQL
  • Provisioning an Azure Data Factory
  • Python for Data Science – Introduction to Python for Data Science
  • Python for Data Science: Advanced Data Visualization Using Seaborn
  • Python for Data Science: Advanced Operations with NumPy Arrays
  • Python for Data Science: Basic Data Visualization Using Seaborn
  • Python for Data Science: Introduction to NumPy for Multi-dimentional Data
  • Python for Data Science: Introduction to Pandas
  • Python for Data Science: Manipulating and Analyzing Data in Pandas DataFrames
  • Quality and Security of Big Data Operations
  • Querying and Manipulating Data
  • R for Data Science: Classification & Clustering
  • R for Data Science: Data Exploration
  • R for Data Science: Data Structures
  • R for Data Science: Data Visualization
  • R for Data Science: Importing and Exporting Data
  • R for Data Science: Regression Methods
  • Random Forests & Uplift Models
  • RavenDB Integration
  • RavenDB Overview
  • Raw Data to Insights: Data Ingestion & Statistical Analysis
  • Raw Data to Insights: Data Management & Decision Making
  • Regression Analysis
  • Research Topics in ML and DL
  • Script Components
  • Scripting with Spotfire
  • Securing Blockchain Implementations
  • Securing Hadoop Clusters
  • Serving Digital Customers with Omnichannel
  • Spark Monitoring and Tuning
  • Spark Security
  • Splunk Administration
  • Splunk Fundamentals
  • Splunk Visualizations and Dashboards
  • Spotfire Automation, Analyzation, and Visualization
  • Spotfire Basics
  • Spotfire Data Combinations
  • Spotfire Visualizations and Relationships
  • SQL Server 2016 Database Objects
  • SQL Server 2016 Indexes and Views
  • SQL Server Database Fundamentals: Creating, Optimizing, and Securing Databases
  • SQL Server Database Fundamentals: Design Principles and Data Manipulation
  • SQL Server Instances and Storage Considerations
  • SQL Server Performance Settings
  • SQL Server Virtual Machines on Azure
  • SQL Tuning, Resource Management, and Job Scheduling in Oracle Database 12c
  • SSIS Components
  • SSIS Package Execution and Script Tasks
  • SSIS Packages
  • SSIS Security
  • SSIS Solutions
  • SSIS Variables
  • Stabilizing Hadoop Clusters
  • Streaming Data Architectures: An Introduction to Streaming Data
  • Streaming Data Architectures: Processing Streaming Data
  • Structured Streaming
  • Subqueries and Predicate
  • T-SQL Querying
  • Tableau Advanced Visualizations
  • Tableau Calculations
  • Tableau Charts
  • Tableau Dashboards and Data Organization
  • Tableau Data Connections
  • Tableau Desktop: Real Time Dashboards
  • Tableau Interface and Sharing
  • Tableau Maps
  • Tableau Scripting
  • Tableau Time Dimensions
  • Tableau Visualization
  • Tableau Visualization Design
  • Teradata Basics: Communication and Database Security
  • Teradata Basics: Data Storage and Access Methods
  • Teradata Basics: Relational Database and Data Warehouse Basics
  • Teradata SQL: DDL, DML, and SQL Optimization
  • Teradata SQL: Functions, Data Conversions, and Working with Time
  • Teradata SQL: The SELECT Statement, Joins, and Subqueries
  • Text Mining & Social Network Analysis
  • The Basics of Blockchain
  • The Big Data Technology Wave
  • The R Language and Big Data Processing
  • Time Series Modeling
  • Transactions and Isolation Levels
  • Trifacta for Data Wrangling: Wrangling Data
  • Triggers and Functions
  • Troubleshooting Data Integration
  • Understanding and Raising Analytics Maturity
  • Understanding the Digital Customer
  • User Security and Auditing in Oracle Database 12c
  • Using Data to Find Data: Correction & Categorization
  • Using Data to Find Data: Data Discovery & Exploration
  • Using Functions in SQL Server 2016
  • Using Your Data with Splunk
  • Working with Bitcoin
  • Working with Cassandra
  • Working with Data for Effective Decision Making
  • Working with Data Mapping, Jobs, and Automation
  • Working with HDInsight Clusters