If you’re looking to get certified in Cybersecurity, IT Security, or Computer Security, then you don’t have as many straight forward options as if you wanted to get certified with Windows or Linux; or even if you want to get certified with Microsoft Azure or Amazon AWS. Those certification paths are quite straight forward, as you can find certifications offered by the appropriate vendors. However, Security certification is a bit more niche. While there are a few options for getting certified in Security, it can be a bit confusing to navigate the landscape of what it offered. This article lists out the available Security certifications available in the industry, and will help clarify any questions you have in regards to deciding which is the most appropriate for you. Read More
There’s so much talk about what certification to get, what exam to pass, what are the requirements, and how to get certified. However, the opposite side of the coin is the older certifications and exam that go away over time. When technologies become obsolete, Microsoft retires certification exams that are no longer as relevant as they once were to make room for the newer certifications coming out with current technologies.
Microsoft does publish the exams they are retiring and the planned retirement date, but the information is a bit hidden / buried within the Microsoft Learning site. As a result, I thought I’d post about the Microsoft Certification Exams that are scheduled to be retired in the second half of 2018 to shed a little light on this to those who may not really be aware. Read More
Microsoft announced, at Inspire 2018, some additions and changes to the Microsoft Certifications surrounding the Microsoft Azure cloud that are starting to be released, and will be expanded upon in the near future around the timing of the Microsoft Ignite 2018 conference in September 2018. These announcements were made in the LER01 – The future of modern learning session at MS Inspire 2018, in addition to a blog post on the Microsoft Learning blog written by Liberty Munson. Read More
Microsoft continually updates the content of the different Microsoft Azure certification exams, but it’s been almost 2 years since they really updated the Microsoft Certification paths to be more Azure focused / integrated. Great news is that Microsoft is making further changes to keep improving the various Microsoft Azure Certifications and associated exams that are offered. During the Microsoft Inspire 2018 conference, the Microsoft Learning team announced the introduction of this brand new Azure certification track tailored for Azure Administrators. Read More
The AZ-102 Microsoft Azure Administrator Certification Transition certification exam tests and validates your expertise as an Azure Administrator around managing cloud services that span storage, security, networking, and compute capabilities within the Microsoft Azure cloud. This exam provides a upgrade / transition path from to the Azure Administrator certification for anyone who has already passed the older, existing 70-533 Implementing Azure Infrastructure Solutions certification exam. Read More
The AZ-101 Microsoft Azure Integration and Security certification exam tests and validates your expertise managing and securing cloud services that span storage, security, networking, and compute capabilities within the Microsoft Azure cloud. This is the second in a set of exams that make up the new Azure Administrator certification track. Read More
The AZ-100 Microsoft Azure Infrastructure and Deployment certification exam tests and validates your expertise as an Azure Administrator around managing cloud services that span storage, security, networking, and compute capabilities within the Microsoft Azure cloud. This is the first in a set of exams that make up the new Azure Administrator certification track. Read More
The 70-777 Implementing Microsoft Azure Cosmos DB Solutions certification exam tests and validates your expertise in designing, building, and troubleshooting Azure Cosmos DB solutions. The exam is focused around the Azure Cosmos DB database service in the Microsoft Azure Cloud, and is targeted towards database developers, big data developers, and architects who are leveraging Azure Cosmos DB in their solutions. Read More
Hi! My name is Chris Pietschmann, and I’m the primary person behind BuildAzure.com and the Build Azure Weekly newsletter. I started BuildAzure.com back in June 2015 after I passed the Azure MCSD certification as an effort for me to be able to focus my Azure blogging efforts into a more targeted fashion. Over time, as a result of my many community contributions, including the success of sharing information on BuildAzure.com, I was awarded the Microsoft MVP award in 2017 in the expertise category of Microsoft Azure.
Most recently, on July 1, 2018, I was re-awarded the Microsoft MVP award for 2018 in the category of Microsoft Azure. While this is my 2nd Microsoft MVP award for Microsoft Azure, it’s actually my 7th time winning the Microsoft MVP award!
The 70-776 Performing Big Data Engineering on Microsoft Cloud Services certification exam tests and validates your expertise in designing analytics solutions and building operationalized solutions on Microsoft Azure. This exam covers data engineering topics around Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics.
Exam Target Audience
The 70-776 Performing Big Data Engineering on Microsoft Cloud Services certification exam is targeted towards Big Data Professionals. This exam is centered around designing analytics solutions and building operationalized solutions on Microsoft Azure. The primary Azure service areas covered on this Big Data exam are: Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics.
Candidates with experience and familiarity with the capabilities and features of batch data processing, real-time processing, and operationalization technologies are the targeted audience for this exam. These candidates will be able to apply Microsoft cloud technologies to solution designs, and implement big data analytics solutions.
Skills Measured
Here is a list of the skills and objectives measured on this exam. The percentages on the high level objective areas represents the percentage of the exam that is focused on that objective area.
Design and Implement Complex Event Processing By Using Azure Stream Analytics (15-20%)
Ingest data for real-time processing
Select appropriate data ingestion technology based on specific constraints; design partitioning scheme and select mechanism for partitioning; ingest and process data from a Twitter stream; connect to stream processing entities; estimate throughput, latency needs, and job footprint; design reference data streams
Design and implement Azure Stream Analytics
Configure thresholds, use the Azure Machine Learning UDF, create alerts based on conditions, use a machine learning model for scoring, train a model for continuous learning, use common stream processing scenarios
Implement and manage the streaming pipeline
Stream data to a live dashboard, archive data as a storage artifact for batch processing, enable consistency between stream processing and batch processing logic
Query real-time data by using the Azure Stream Analytics query language
Use built-in functions, use data types, identify query language elements, control query windowing by using Time Management, guarantee event delivery
Design and Implement Analytics by Using Azure Data Lake (25-30%)
Ingest data into Azure Data Lake Store
Create an Azure Data Lake Store (ADLS) account, copy data to ADLS, secure data within ADLS by using access control, leverage end-user or service-to-service authentication appropriately, tune the performance of ADLS, access diagnostic logs
Manage Azure Data Lake Analytics
Create an Azure Data Lake Analytics (ADLA) account, manage users, manage data sources, manage, monitor, and troubleshoot jobs, access diagnostic logs, optimize jobs by using the vertex view, identify historical job information
Extract and transform data by using U-SQL
Schematize data on read at scale; generate outputter files; use the U-SQL data types, use C# and U-SQL expression language; identify major differences between T-SQL and U-SQL; perform JOINS, PIVOT, UNPIVOT, CROSS APPLY, and Windowing functions in U-SQL; share data and code through U-SQL catalog; define benefits and use of structured data in U-SQL; manage and secure the Catalog
Extend U-SQL programmability
Use user-defined functions, aggregators, and operators, scale out user-defined operators, call Python, R, and Cognitive capabilities, use U-SQL user-defined types, perform federated queries, share data and code across ADLA and ADLS
Integrate Azure Data Lake Analytics with other services
Integrate with Azure Data Factory, Azure HDInsight, Azure Data Catalog, and Azure Event Hubs, ingest data from Azure SQL Data Warehouse
Design and Implement Azure SQL Data Warehouse Solutions (15-20%)
Design tables in Azure SQL Data Warehouse
Choose the optimal type of distribution column to optimize workflows, select a table geometry, limit data skew and process skew through the appropriate selection of distributed columns, design columnstore indexes, identify when to scale compute nodes, calculate the number of distributions for a given workload
Query data in Azure SQL Data Warehouse
Implement query labels, aggregate functions, create and manage statistics in distributed tables, monitor user queries to identify performance issues, change a user resource class
Integrate Azure SQL Data Warehouse with other services
Ingest data into Azure SQL Data Warehouse by using AZCopy, Polybase, Bulk Copy Program (BCP), Azure Data Factory, SQL Server Integration Services (SSIS), Create-Table-As-Select (CTAS), and Create-External-Table-As-Select (CETAS); export data from Azure SQL Data Warehouse; provide connection information to access Azure SQL Data Warehouse from Azure Machine Learning; leverage Polybase to access a different distributed store; migrate data to Azure SQL Data Warehouse; select the appropriate ingestion method based on business needs
Design and Implement Cloud-Based Integration by using Azure Data Factory (15-20%)
Implement datasets and linked services
Implement availability for the slice, create dataset policies, configure the appropriate linked service based on the activity and the dataset
Move, transform, and analyze data by using Azure Data Factory activities
Copy data between on-premises and the cloud, create different activity types, extend the data factory by using custom processing steps, move data to and from Azure SQL Data Warehouse
Orchestrate data processing by using Azure Data Factory pipelines
Identify data dependencies and chain multiple activities, model schedules based on data dependencies, provision and run data pipelines, design a data flow
Monitor and manage Azure Data Factory
Identify failures and root causes, create alerts for specified conditions, perform a redeploy, use the Microsoft Azure Portal monitoring tool
Manage and Maintain Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics (20-25%)
Provision Azure SQL Data Warehouse, Azure Data Lake, Azure Data Factory, and Azure Stream Analytics
Provision Azure SQL Data Warehouse, Azure Data Lake, and Azure Data Factory, implement Azure Stream Analytics
Implement authentication, authorization, and auditing
Integrate services with Azure Active Directory (Azure AD), use the local security model in Azure SQL Data Warehouse, configure firewalls, implement auditing, integrate services with Azure Data Factory
Manage data recovery for Azure SQL Data Warehouse, Azure Data Lake, and Azure Data Factory, Azure Stream Analytics
Backup and recover services, plan and implement geo-redundancy for Azure Storage, migrate from an on-premises data warehouse to Azure SQL Data Warehouse
Monitor Azure SQL Data Warehouse, Azure Data Lake, and Azure Stream Analytics
Manage concurrency, manage elastic scale for Azure SQL Data Warehouse, monitor workloads by using Dynamic Management Views (DMVs) for Azure SQL Data Warehouse, troubleshoot Azure Data Lake performance by using the Vertex Execution View
Design and implement storage solutions for big data implementations
Optimize storage to meet performance needs, select appropriate storage types based on business requirements, use AZCopy, Storage Explorer and Redgate Azure Explorer to migrate data, design cloud solutions that integrate with on-premises data
You can also view the full objectives list for the 70-776 Performing Big Data Engineering on Microsoft Cloud Services certification exam on the official 70-776 exam page at Microsoft.com.
Training Material
There are not very many study / training materials designed specifically for the 70-776 Perform Big Data Engineering on Microsoft Cloud Services certification exam. As example, Microsoft Press has not published any Exam Ref or Guide books for this exam yet (at the time of writing this.) However, there is still plenty of material available from various sources, both Free and Paid, that range from official product documentation from Microsoft, other articles and videos from Microsoft, as well as training from companies like Opsgility and their SkillMeUp service.
Another interesting resource to utilize is the following recording of the 70-776 Cert Exam Prep session given by James Herring at Microsoft Ignite 2017:
The 70-777 Implementing Microsoft Azure Cosmos DB Solutions certification exam tests and validates your expertise in designing, building, and troubleshooting Azure Cosmos DB solutions. The exam is focused around the Azure Cosmos DB database service in the Microsoft Azure Cloud, and is targeted towards database developers, big data developers, and architects who are leveraging Azure Cosmos DB in their solutions. 
Hi! My name is Chris Pietschmann, and I’m the primary person behind BuildAzure.com and the Build Azure Weekly newsletter. I started BuildAzure.com back in June 2015 after I passed the