Expert Courses

SQL Expert

NoSQL to SQL Integration: Explore techniques for integrating SQL databases with NoSQL data stores (e.g., MongoDB, Cassandra) using tools like Apache Kafka, Apache Spark, or custom ETL pipelines, enabling hybrid data processing and analytics workflows.
Data Virtualization and Federated Queries: Master data virtualization techniques for querying and integrating data from diverse sources (e.g., databases, data lakes, APIs) using federated queries and SQL-based data virtualization platforms.
Blockchain and Cryptocurrency Data Queries: Gain expertise in querying and analyzing blockchain and cryptocurrency data using SQL-based tools and techniques, including blockchain-specific query languages (e.g., Solidity for Ethereum) and smart contract interactions.

Advanced Query Optimization Techniques: Dive deep into the inner workings of query optimization, exploring techniques such as query plan analysis, cost-based optimization, and hints or directives to guide the query optimizer.
SQL Injection Prevention: Master techniques for preventing SQL injection attacks, including parameterized queries, input validation, and proper privilege management to mitigate security risks.

Database Internals and Performance Tuning: Gain a thorough understanding of database internals, including storage engines, buffer management, query processing, and transaction management. Learn advanced performance tuning techniques, including index selection, query rewriting, and database parameter optimization.
Temporal and Bi-temporal Data Modeling: Explore advanced techniques for modeling temporal data, including system-versioned temporal tables, bitemporal tables, and managing time-varying data with effective dating and versioning strategies.

Advanced Window Functions: Master complex window function usage, including advanced window frame specifications, window function nesting, and partitioning strategies for sophisticated analytics and reporting.
Graph Database Queries: Learn about graph database concepts and query languages, enabling advanced graph-based querying and analysis for applications such as social networks, recommendation systems, and network analysis.
Geospatial Queries: Deepen your understanding of SQL extensions for geospatial data types and spatial query operators, enabling advanced geospatial analysis and mapping applications.

Temporal and Spatial Indexing: Explore advanced indexing techniques tailored for temporal and spatial data, including R-tree, quadtree, and geohash indexing, to optimize query performance for temporal and spatial queries.
Data Mining and Machine Learning Integration: Integrate SQL with data mining and machine learning frameworks (e.g., R, Python) to perform advanced analytics, predictive modeling, and pattern recognition directly within the database environment.
Advanced Analytics with SQL Extensions: Explore SQL extensions for advanced analytics, including statistical functions, time series analysis, sentiment analysis, natural language processing (NLP), and machine learning algorithms for clustering, classification, and regression.

Database Scalability and High Availability: Learn advanced techniques for database scalability and high availability, including database sharding, replication, failover clustering, and distributed database architectures for handling large-scale deployments and ensuring continuous availability.
Database Security and Compliance: Deepen your knowledge of database security principles and compliance requirements, including encryption, access control, auditing, data masking, and regulatory frameworks such as GDPR, HIPAA, and PCI-DSS.

Completion of Power BI Advanced
Mastery of advanced Power BI functionalities and features
Experience with optimizing data models for performance
Understanding of advanced DAX functions and optimization
Familiarity with integrating Power BI with other tools and services (e.g., Power Apps, Azure)
Knowledge of best practices in data governance and security within Power BI

Power BI Embedded : Define Power BI Embedded
Power Bi Embedded Conceptual Model : Explain Power Bi Embedded Conceptual Model

SSRS 2016 Installation : Installation of SQL Server 2016 along with SSRS
- Features of SSRS 2016 : Express features of SSRS 2016
- Register SSRS : Registration of SSRS with Power BI account
- SSRS visuals : PIN SSRS visuals with SQL Server agent

APIs : Define and Differentiate REST API and .NET API
Authentication and Authorization : Explain How to authenticate and Authorize Row Level Security with Embedded Power BI
Iframe : Illustrate How to Embed a Power BI report with an I Frame