Microsoft Azure DP-203

Master Data Storage Strategies with Tech Cryptors'

Microsoft Azure DP-203

Tech Cryptors provide unparalleled customer satisfaction and exceptional value for clients.

Discover the world of data storage strategies with Tech Cryptors’ Microsoft Azure DP-203 course. Dive deep into partitioning strategies, data transformation techniques, and efficient pipeline management on Microsoft Azure. Unlock the skills to optimize, secure, and harness the potential of Azure’s data storage and processing capabilities for enhanced insights and strategic decision-making. Our cutting-edge courses are designed to equip aspiring professionals with practical skills and knowledge to excel in the dynamic world of networking.

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Understanding Design and Implement Data Storage in Microsoft Azure DP-203

Files Partition Strategy: Create and utilize a strategy to efficiently manage file partitions.

Analytical Workloads Partition Strategy: Design a partition strategy optimized for analytical workloads.

Streaming Workloads Partition Strategy: Implement a partition strategy tailored for streaming workloads.

Azure Synapse Analytics Partition Strategy: Develop a partitioning approach suitable for Azure Synapse Analytics.

Partitioning in Azure Data Lake Storage Gen2: Recognize scenarios demanding partitioning in Azure Data Lake Storage Gen2.

Query Execution and Template Implementation in Microsoft Azure DP-203

Query Execution with Compute Solutions: Utilize SQL serverless and Spark clusters to create and run queries.

Azure Synapse Analytics Database Templates: Recommend and apply database templates in Azure Synapse Analytics.

Data Lineage Updates: Push updated data lineage to Microsoft Purview for enhanced data tracking.

Browsing Metadata: Browse and search metadata using Microsoft Purview Data Catalog.

Learning to Develop Data Processing Solutions in Microsoft Azure DP-203

Understanding Data Transformation in Microsoft Azure DP-203

Incremental Loads: Design and implement strategies for incremental data loading.

Apache Spark Transformation: Utilize Apache Spark for efficient data transformation.

Transact-SQL (T-SQL) Transformation: Apply Transact-SQL within Azure Synapse Analytics for data transformation.

Will I Get certification after completing this course?

Yes. Tech Cryptors is ISO 9001:2015 CERTIFIED COMPANY under IAF. Also, we are in collaboration with Shastra INDIAN INSTITUTES TECHNOLOGY Madras. CERTIFICATION will have the significance of the above.

This course is available in Offline Mode or Online Mode?

We conduct this course in BOTH online and offline modes. You can choose the mode suitable for you, even you can SWITCH modes for a couple of lectures in case of any personal issues and emergencies.

One Batch will be accommodated with how many students?

In one batch we allow MAXIMUM 4 students Because we believe that to have a better understanding and to excel in this course PERSONAL ATTENTION is needed.

From When a new batch is starting? and what will be the timmings for the same?

We have new batches starting every 15 days, But you should register asap for your desired date because our batches are filling fast. Batch timings are also kept AS PER YOUR TIME CONVENIENCE, we don’t have any rigid preassigned slots.

How to register for this course? and where to know about Fees and other Queries.

Well, you can SCROLL DOWN and click on WHATSAPP CHAT text OR CLICK HERE to talk with our customer care executive. We are happy to help you with all of your questions and details.

Azure Synapse Pipelines and Data Factory: Use Azure Synapse Pipelines or Azure Data Factory for data ingestion and transformation.

Azure Stream Analytics Transformation: Transform data using Azure Stream Analytics.

Data Cleansing: Cleanse data to ensure quality and consistency.

Handling Duplicates, Missing Data, and Late-Arriving Data: Develop strategies to manage these data challenges.

Data Splitting and JSON Shredding: Split and shred JSON data for efficient processing.

Data Encoding and Decoding: Implement data encoding and decoding techniques.

Error Handling and Data Normalization: Configure error handling and normalize data for accuracy.

Data Exploration: Perform exploratory analysis to gain insights in Microsoft Azure DP-203.

Batch Processing with Azure Services: Develop batch processing solutions using Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, and Azure Data Factory.

PolyBase Data Loading: Load data to a SQL pool using PolyBase.

Azure Synapse Link Utilization: Query replicated data through Azure Synapse Link.

Pipeline Creation and Scaling: Build data pipelines and scale resources accordingly.

Batch Size Configuration and Testing: Configure batch sizes and create tests for pipelines.

Notebook Integration: Integrate Jupyter or Python notebooks into pipelines.

Data Upsertion and Reversion: Manage data upserts and reversions effectively.

Exception Handling and Batch Retention: Implement error handling and manage batch retention.

Delta Lake Operations: Read from and write to a delta lake.

Creating Stream Processing Solutions in Microsoft Azure DP-203

Stream Processing with Azure Services in Microsoft Azure DP-203

Stream Processing with Stream Analytics: Build stream processing solutions using Stream Analytics and Azure Event Hubs.

Structured Streaming with Spark: Process data using Spark structured streaming.

Windowed Aggregates: Create windowed aggregates for stream processing.

Schema Drift Handling: Address schema drift challenges.

Time Series Data Processing: Process time series data efficiently.

Partition-Based and Intra-Partition Processing: Process data across and within partitions.

Checkpoint and Watermark Configuration: Configure checkpoints and watermarking during processing.

Learn Optimization and Troubleshooting in Microsoft Azure DP-203

Resource Scaling and Performance Optimization: Optimize pipelines for analytical and transactional goals.

Interrupt Handling and Exception Management: Manage interruptions and exceptions during processing.

Data Upsertion and Archived Data Replay: Implement upsertion and replay archived stream data.

Batch Triggering and Failure Handling: Handle batch triggers and manage failed batch loads.

Validation and Monitoring of Batch Loads: Validate and monitor batch load operations.

Pipeline Management and Scheduling: Manage and schedule data pipelines using Azure Data Factory or Azure Synapse Pipelines.

Version Control for Pipeline Artifacts: Implement version control for pipeline artifacts.

Spark Job Management: Manage Spark jobs within pipelines.

Ensuring Secure, Monitored, and Optimized Data Processing

Understanding Security and Access Control

Data Masking and Encryption: Implement data masking and encrypt data at rest and in motion.

Row and Column-Level Security: Apply security measures at row and column levels.

Azure RBAC and ACLs: Implement Azure role-based access control (RBAC) and ACLs for Data Lake Storage Gen2.

Data Retention Policy: Enforce a data retention policy to manage data lifecycle.

Secure Endpoints: Configure private and public secure endpoints.

Resource Tokens in Azure Databricks: Implement resource tokens for secure access in Azure Databricks.

Sensitive Data Handling: Load and write sensitive data securely.

Learn about Monitoring and Optimization in Microsoft Azure DP-203

Azure Monitor Logging: Implement logging for Azure Monitor.

Monitoring Services Configuration: Configure monitoring services for effective performance tracking.

Stream Processing Monitoring: Monitor stream processing activities in Microsoft Azure DP-203.

Performance Measurement: Measure data movement and query performance.

Pipeline Testing and Monitoring: Schedule and monitor pipeline tests.

Azure Monitor Metrics and Logs Interpretation: Understand and interpret Azure Monitor metrics and logs.

Pipeline Alert Strategy: Develop an alert strategy for pipelines in Microsoft Azure DP-203.

File Optimization: Compact small files to improve storage efficiency.

Skew Handling and Data Spill Management: Address data skew and manage data spill.

Resource Management Optimization: Optimize resource management for efficient processing.

Query Tuning with Indexers and Cache: Tune queries using indexers and caching.

Troubleshooting Failed Spark Jobs and Pipelines: Troubleshoot and resolve issues with failed Spark jobs and pipeline runs, including external service activities.

Note For Certification

TECH CRYPTORS is an ISO 9001:2015 CERTIFIED COMPANY, also in COLLABORATION with shaastra, INDIAN INSTITUTE OF TECHNOLOGY, madras. Certification will be with Significance of above for attended TRAINING COURSE. Also, every certificate will have a Unique Certificate Number, which will be helpful WORLDWIDE to verify the validity of every individual certificate using www.techcryptors.com.

Microsoft Azure DP-203