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70-777: Implementing Microsoft Azure Cosmos DB Solutions Exam Certified Professional salary

The average salary of a 70-777: Implementing Microsoft Azure Cosmos DB Solutions Exam Certified Expert in

• India - 15,00,327 INR
• Europe - 80,347 EURO
• United State - 90,247 USD
• England - 70,632 POUND

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Topics of 70-777: Implementing Microsoft Azure Cosmos DB Solutions Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our 70-348:Managing Projects and Portfolios with Microsoft exam dumps will include the following topics:

1. Partition and Model Data

Plan a partitioning strategy

• Select a partition key for a container; differentiate between partition keys and partition key ranges; partition data across multiple containers; calculate throughput distribution across partition key ranges; control cross-partition queries; plan for transactions

Model data based on business use cases

• Identify when to co-locate data within the same container or across multiple containers; identify when to co-locate data within the same partition key or across multiple partition keys; identify when to co-locate data within the same document or across multiple documents; share properties between documents

2. Replicate Data Across the World

Implement global distribution and high availability

• Replicate data to additional regions; define automatic failover policies for disaster recovery; perform manual failovers to change the write region; set the preferred location of applications for low-latency access; design patterns for multi-write regions; resolve conflicts surfaced by the conflict feed

Select a data consistency approach based on business use cases

• Identify use cases for consistencies; differentiate between consistencies by using characteristics; differentiate between consistencies by using trade-offs between performance and consistency; use session tokens

3. Tune and Debug Azure Cosmos DB Solutions

Estimate and provision request units

• Differentiate requests and request units; retrieve request unit cost of an operation; estimate request unit allocation for a container; tune throughput for uneven workloads and manage throttling; monitor Azure portal metrics; recommend solutions based on query metrics

Tune container settings

• Manage lifecycle of data by using TTL; tune an index policy; include and exclude properties from index paths

Implement security

• Secure access to data; rotate keys; understand encryption at rest and in transit; configure IP firewalls; create and manage users; configure fine-grained access to resources

Debug a Cosmos DB solution

• Configure diagnostic logging; recommend solutions based on data retrieved from logs; evaluate response status code categories; throttle; review metrics and performance tips

4. Perform Integration and Develop Solutions

Develop applications with the SQL API

• Optimize SDK and concurrency control; Tune request options for CRUD and queries; examine response headers; implement optimistic concurrency control with ETAG; query geospatial data; use advanced SQL query operators for complex documents (nested objects and arrays); perform intra-document JOINs; perform SQL queries; implement user-defined functions; use multi-record transactions with stored procedures; implement a continuation model for bounded execution with stored procedures; implement server-side logic and transactions

Migrate from MongoDB to MongoDB API in Cosmos DB

• Choose appropriate tools to migrate data; transfer data

Implement event-driven applications by using Azure functions, triggers and Cosmos DB change feed

• Use Cosmos DB triggers for Azure functions; change feed mechanics

Analyze Cosmos DB data with Apache Spark connector

• Set up and configure a Cosmos DB Spark connector; push down predicates