How difficult is the Google Cloud Digital Leader Exam?

The Google Cloud Digital Leader Exam is a certification exam offered by Google Cloud. It is designed to test an individual’s understanding of cloud computing concepts and their ability to apply those concepts to solve business problems. The exam covers a range of topics, including cloud computing basics, cloud services, data analysis, machine learning, and security.

The exam is intended for business leaders, IT professionals, and anyone interested in learning about Google Cloud technologies. It is a multiple-choice exam that can be taken online, and the passing score is 70%. Successful completion of the exam results in a Google Cloud Digital Leader certification, which demonstrates a foundational understanding of cloud computing concepts and how they can be applied in a business context.

Google Cloud Digital Leader Exam Glossary

Here are some terms that may be helpful to know when preparing for the Google Cloud Digital Leader Exam:

Cloud computing: The delivery of computing resources, including servers, storage, databases, networking, software, analytics, and intelligence, over the internet.
Infrastructure as a Service (IaaS): A type of cloud computing service that provides virtualized computing resources over the internet.
Platform as a Service (PaaS): A type of cloud computing service that provides a platform for developing and deploying applications over the internet.
Software as a Service (SaaS): A type of cloud computing service that provides software applications over the internet.
Public cloud: A type of cloud computing service that provides computing resources over the internet to the general public.
Private cloud: A type of cloud computing service that provides computing resources over a private network to a specific organization.
Hybrid cloud: A type of cloud computing service that combines public and private clouds to provide a more flexible and scalable computing environment.
Machine learning: A type of artificial intelligence that allows computers to learn and improve from experience without being explicitly programmed.
Big data: Extremely large datasets that can be analyzed to reveal patterns, trends, and associations.
Data analytics: The process of analyzing and interpreting data to gain insights and make informed decisions.
Security: The practice of protecting computer systems and data from unauthorized access, theft, and damage.
Cloud storage: A service that allows data to be stored, accessed, and managed over the internet.
Learn Cloud networking: A service that allows computing resources to be connected and communicated over the internet.
Cloud migration: The process of moving applications, data, and other business elements from a local computing environment to a cloud computing environment.

Google Cloud Digital Leader Study Guide

Here are some official resources that can help you prepare for the Google Cloud Digital Leader Exam:

Google Cloud Learning Center: This is the official learning platform for Google Cloud, which offers free online courses, tutorials, and hands-on labs to help you learn about Google Cloud technologies. You can access it at https://cloud.google.com/training.
Google Cloud Certification: This is the official certification page for Google Cloud, where you can learn more about the various certification exams, including the Digital Leader Exam. You can access it at https://cloud.google.com/certification.
Google Cloud documentation: This is the official documentation for Google Cloud products and services, which provides detailed information on how to use them. You can access it at https://cloud.google.com/docs.
Google Cloud blog: This is the official blog for Google Cloud, which provides updates and insights on Google Cloud technologies. You can access it at https://cloud.google.com/blog.
Google Cloud community: This is the official community for Google Cloud, where you can connect with other Google Cloud users and experts to ask questions and share knowledge. You can access it at https://cloud.google.com/community.

Google Cloud Digital Leader Exam Tips and Tricks

Here are some tips and tricks that can help you prepare for the Google Cloud Digital Leader Exam:

Understand the exam format: The Google Cloud Digital Leader Exam is a multiple-choice exam that consists of 50 questions. You will have 1 hour to complete the exam. Make sure you understand the format of the exam before you start preparing.
Review the exam guide: The exam guide provides a detailed overview of the topics covered in the exam, as well as the skills and knowledge required to pass the exam. Review the exam guide carefully to ensure that you are familiar with all the topics covered in the exam.
Take practice exams: Practice exams can help you assess your knowledge and identify areas where you need to improve. Use the official Google Cloud practice exams to prepare for the exam and gauge your readiness.
Join the Google Cloud community: The Google Cloud community is a great resource for learning about Google Cloud technologies and getting help from other users and experts. Join the community to ask questions, share knowledge, and connect with other Google Cloud users.
Focus on key topics: Make sure you have a deep understanding of key topics such as Google Cloud infrastructure, security, networking, and data management. Spend extra time studying these topics to ensure that you are well-prepared for the exam.
Stay calm and focused: Don’t panic if you encounter a difficult question during the exam. Stay calm and focused, and take the time to think through the question and come up with the best possible answer.

Is the Google Cloud Digital Leader Exam difficult?

We are aware of how challenging can be the Google Cloud Digital Leader Exam for those who are new to the cloud. You must concentrate on how distinctive your preparation is and what study tools/training you are using to minimize this. The best course of action is to start with the exam topic areas. In other words, this test confirms your understanding of your capacity for working with technical specialists. You must get a solid understanding of Google Cloud’s role in digital transformation and data-driven innovation.

This exam will not be challenging for you if you have knowledge of the following topics. And, to assist you to become a Google Cloud Digital Leader, we’ll explore the various study methods and exam blueprints in the next section.

Steps to prepare for Cloud Digital Leader Exam

Let us now look at the steps to prepare for the exam –

1. Getting familiar with the exam guide

You can check if your abilities align with the test’s objectives by reviewing the comprehensive list of topics that may be cover in the exam in the Google Cloud Digital Leader guide.

Section 1: Digital Transformation with Google Cloud (~17% of the exam)

1.1 Why Cloud Technology is Transforming Business

● Explain why and how the cloud is revolutionizing businesses. (Google Documentation: What is Digital Transformation?)

a. Define the terms: cloud, cloud technology, data, digital transformation, cloud-native, open source, open standard. (Google Documentation: What is cloud native?)

b. Describe the differences between cloud technology and traditional or on-premises technology.

c. Explain the benefits of cloud technology to a business’ digital transformation: this technology is scalable, flexible, agile, secure, cost-effective and offers strategic value. (Google Documentation: Advantages and Disadvantages of Cloud Computing)

d. Describe the primary benefits of on-premises infrastructure, public cloud, private cloud, hybrid cloud, and multicloud and differentiate between them. (Google Documentation: What is multicloud?)

e. Describe the main business transformation benefits of Google Cloud: intelligence, freedom, collaboration, trust, and sustainability. (Google Documentation: Why Google Cloud)

f. Describe the implications and risks for organizations that do not adopt new technology. (Google Documentation: Advantages and Disadvantages of Cloud Computing)

g. Describe the drivers and challenges that lead organizations to undergo a digital transformation. (Google Documentation: What is Digital Transformation?)

h. Describe the transformation cloud and how it accelerates an organization’s digital transformation through app and infrastructure modernization, data democratization, people connections, and trusted transactions. (Google Documentation: Reinventing the future with a transformation cloud)

1.2 Fundamental Cloud Concepts

● Explain general cloud concepts. (Google Documentation: Google Cloud overview)

a. Describe how transitioning to a cloud infrastructure affects flexibility, scalability, reliability, elasticity, agility, and total cost of ownership (TCO). Apply these concepts to various business use cases.

b. Explain how an organization’s transition from an on-premises environment to the cloud shifts their capital expenditures (CapEx) to operational expenditures (OpEx), and how that affects their total cost of ownership (TCO).

c. Identify when private, hybrid, or multicloud infrastructures best apply to different business use cases. (Google Documentation: Distributed, hybrid, and multicloud overview)

d. Define basic network infrastructure terminology, including: IP address; internet service provider (ISP); domain name server (DNS), regions, and zones; fiber optics; subsea cables; network edge data centers, latency; and bandwidth. (Google Documentation: Google Cloud Networking overview)

e. Discuss how Google Cloud supports digital transformation with global infrastructure and data centers connected by a fast, reliable network. (Google Documentation: Google Cloud infrastructure)

1.3 Cloud Computing Models and Shared Responsibility

● Discuss the benefits and tradeoffs of using infrastructure as a service (IaaS); platform as a service (PaaS); and software as a service (SaaS). (Google Documentation: PaaS vs. IaaS vs. SaaS vs. CaaS)

a. Define IaaS, PaaS, and SaaS. (Google Documentation: PaaS vs. IaaS vs. SaaS vs. CaaS)

b. Compare and contrast the benefits and tradeoffs of IaaS, PaaS, and SaaS including total cost of ownership (TCO), flexibility, shared responsibilities, management level, and necessary staffing and technical expertise.

c. Determine which computing model (IaaS, PaaS, SaaS) applies to various business scenarios and use cases.

d. Describe the cloud shared responsibility model. Compare which responsibilities are the cloud provider’s, and which responsibilities are the customer’s for on-premises and cloud computing models (IaaS, PaaS, SaaS). (Google Documentation: Shared responsibilities and shared fate on Google Cloud)

Section 2: Exploring Data Transformation with Google Cloud (~16% of the exam)

2.1 The Value of Data

● Describe the intrinsic role that data plays in an organizations’ digital transformation. (Google Documentation: What is Digital Transformation?)

a. Explain how data generates business insights, drives decision making, and creates new value. (Google Documentation: What is Big Data?)

b. Differentiate between basic data management concepts, in particular: databases; data warehouses; data lakes. (Google Documentation: What is a Data Lake?)

c. Explain how organizations can create value by using their current data, collecting new data, and sourcing data externally. (Google Documentation: Integrate your data sources with Data Catalog, What is Data Governance?)

d. Describe how the cloud unlocks business value from all types of data, including structured data and previously untapped unstructured data. (Google Documentation: What is a data cloud?)

e. Discuss the main data value chain concepts and terms.

f. Explain how data governance is essential to a successful data journey. (Google Documentation: What is Data Governance?)

2.2 Google Cloud Data Management Solutions

● Determine which Google Cloud data management products are applicable to different business use cases.

a. Differentiate between Google Cloud data management options including data type and common business use case, including: Cloud Storage; Cloud Spanner; Cloud SQL; Cloud Bigtable; BigQuery; Firestore. (Google Documentation: Google Cloud database options, explained)

b. Define key data management concepts and terms, including: relational; non-relational; object storage; structured query language (SQL); NoSQL. (Google Documentation: What is a NoSQL database?)

c. Describe the benefits of using BigQuery as a serverless, managed data warehouse and analytics engine that can be used in a multicloud environment. (Google Documentation: BigQuery overview)

d. Differentiate between storage classes in Cloud Storage regarding cost and frequency of access, including: Standard; Nearline; Coldline; Archive. (Google Documentation: Storage classes)

e. Describe the ways that an organization can migrate or modernize their current database in the cloud. (Google Documentation: Migration and modernization tools)

2.3 Making Data Useful and Accessible

● Discuss how smart analytics, business intelligence tools, and streaming analytics can add value in different business use cases. (Google Documentation: What is Business Intelligence?, What is streaming analytics?)

a. Describe how Looker democratizes access to data by empowering individuals to self-serve business intelligence and create insights. (Google Documentation: Analyze governed data, deliver business insights, and build AI-powered applications)

b. Discuss the value of analyzing and visualizing data from BigQuery in Looker to create real-time reports, dashboards, and integrating data into workflows. (Google Documentation: Analyze data with Looker Studio, Analyze data with BI Engine and Looker)

c. Describe how streaming analytics in real time makes data more useful and generates business value. (Google Documentation: What is streaming analytics?, Streaming analytics)

d. Describe the main Google Cloud products that modernize data pipelines, including Pub/Sub and Dataflow. (Google Documentation: Dataflow overview, Work with Dataflow data pipelines)

Section 3: Innovating with Google Cloud Artificial Intelligence (~16% of the exam)

3.1 AI and ML Fundamentals

● Discuss the main AI and ML concepts, and explain how ML can create business value. (Google Documentation: Machine learning workflow)

a. Define artificial intelligence (AI) and machine learning (ML).

b. Differentiate the capabilities of AI and ML from data analytics and business intelligence. (Google Documentation: Artificial intelligence (AI) vs. machine learning (ML))

c. Discuss the types of problems that ML can solve. (Google Documentation: What is Machine Learning (ML)?, Problem-solving with ML: automatic document classification)

d. Explain the business value ML creates, including: ability to work with large datasets; scaling business decisions; and unlocking unstructured data.

e. Explain why high-quality, accurate data is essential for successful ML models.

f. Discuss the importance of explainable and responsible AI (Google Documentation: Responsible AI)

3.2 Google Cloud’s AI and ML solutions

● Discuss the range of Google Cloud AI and ML solutions and products available, and how to select the most appropriate solution for different business use cases. (Google Documentation: AI and machine learning solutions)

a. Explain which decisions and tradeoffs organizations need to consider when selecting Google Cloud AI/ML solutions and products, including: speed; effort; differentiation; required expertise.

b. Discuss which Google Cloud AI and ML solutions and products might apply given different business use cases, including: pre-trained APIs; AutoML; build custom models. (Google Documentation: AI and machine learning products, AutoML)

3.3 Building and using Google Cloud AI and ML solutions

● Explain how Google Cloud’s pre-trained API, AutoML, and custom AI/ML products can create business value. (Google Documentation: AutoML)

a. Discuss how BigQuery ML lets users create and execute machine learning models in BigQuery by using standard SQL queries. (Google Documentation: Create machine learning models in BigQuery ML, Introduction to AI and ML in BigQuery)

b. Select which Google Cloud pre-trained API best applies to different business use cases, including: Natural Language API, Vision API, Cloud Translation API, Speech-to-Text API, and Text-to-Speech API. (Google Documentation: Natural Language AI, Translate docs, audio, and videos in real time with Google AI)

c. Explain how an organization can create business value by using their own data to train custom ML models with AutoML.

d. Discuss how building custom models by using Google Cloud’s Vertex AI can create opportunities for business differentiation. (Google Documentation: Introduction to Vertex AI)

e. Recognize TensorFlow as an end-to-end open source set of tools for building and training machine learning models and that Cloud Tensor Processing Unit (TPU) is Google’s proprietary hardware optimized for TensorFlow and ML performance. (Google Documentation: Accelerate AI development with Google Cloud TPUs)

Section 4: Modernize Infrastructure and Applications with Google Cloud (~17% of the exam)

4.1 Cloud modernization and migration

● Explain why modernization and migration to the cloud are important steps in an organization’s transformation journey, and how each application might have a different path. (Google Documentation: Modernization path for .NET applications on Google Cloud)

a. Discuss benefits of infrastructure modernization and application modernization by using Google Cloud. (Google Documentation: Infrastructure modernization)

b. Define the main cloud migration terms, including: workload; retire; retain; rehost; lift and shift; replatform; move and improve; refactor; reimagine. (Google Documentation: Migrate to Google Cloud: Get started)

4.2 Computing in the cloud

● Discuss the options for and advantages of running compute workloads in the cloud. (Google Documentation: Choose a Compute Engine deployment strategy for your workload)

a. Define the main cloud compute terms, including: virtual machines (VMs); containerization; containers; microservices; serverless computing; preemptible VMs; Kubernetes, autoscaling, load balancing. (Google Documentation: Load balancing and scaling)

b. Describe the benefits and business value of running compute workloads in the cloud. (Google Documentation: Advantages and Disadvantages of Cloud Computing)

c. Explain the choices and constraints between different compute options. (Google Documentation: Choosing the right compute option in GCP: a decision tree)

d. Discuss the business value of using Compute Engine to create and run virtual machines on Google’s infrastructure. (Google Documentation: Compute Engine)

e. Discuss the business value of choosing a rehost migration path for specialized legacy applications.

4.3 Serverless computing

● Discuss the advantages of serverless computing in application modernization. (Google Documentation: Serverless)

a. Explain the benefits of serverless computing. (Google Documentation: What is serverless computing?)

b. Discuss the business value of using serverless computing Google Cloud products, including: Cloud Run; App Engine; Cloud Functions. (Google Documentation: Cloud Functions overview)

4.4 Containers in the cloud

● Discuss the advantages of using containers in application modernization. (Google Documentation: Benefits of migrating to containers)

a. Discuss the advantages of modern cloud application development. (Google Documentation: Advantages and Disadvantages of Cloud Computing)

b. Differentiate between virtual machines and containers. (Google Documentation: Containers vs VMs (virtual machines): What are the differences?)

c. Discuss the main benefits of containers and microservices for application modernization. (Google Documentation: Cloud Application Modernization, What is Microservices Architecture?)

d. Discuss the business value of using Google Cloud products to deploy containers, including: Google Kubernetes Engine (GKE); Cloud Run. (Google Documentation: Use GKE and Cloud Run together)

4.5 The value of APIs

● Explain the business value of application programming interfaces (APIs). (Google Documentation: What is API management?)

a. Define application programming interface (API). (Google Documentation: Google Cloud APIs)

b. Explain how organizations can create new business opportunities by exposing and monetizing public-facing APIs.

c. Discuss the business value of using Apigee API Management. (Google Documentation: What is Apigee?)

4.6 Hybrid and multi-cloud

● Discuss the business reasons for choosing hybrid or multi-cloud strategies and how Anthos enables these strategies. (Google Documentation: What is multicloud?)

a. Discuss the reasons and use cases for why organizations choose a hybrid cloud or multi-cloud strategy. (Google Documentation: What is a Hybrid Cloud?)

b. Describe the business value of using Anthos as a single control panel for the management of hybrid or multicloud infrastructure.

Section 5: Trust and Security with Google Cloud (~17% of the exam)

5.1 Trust and security in the cloud

● Discuss fundamental cloud security concepts. (Google Documentation: Google security overview)

a. Describe today’s top cybersecurity threats and business implications.

b. Differentiate between cloud security and traditional on-premises security. (Google Documentation: Cloud network security)

c. Describe the importance of control, compliance, confidentiality, integrity, and availability in a cloud security model. (Google Documentation: Google security overview)

d. Define key security terms and concepts.

5.2 Google’s trusted infrastructure

● Explain the business value of Google’s defense-in-depth multilayered approach to infrastructure security. (Google Documentation: Infrastructure Security in Google Cloud)

a. Describe the benefits of Google designing and building its own data centers, using purpose-built servers, networking, and custom security hardware / software. (Google Documentation: Google infrastructure security design overview)

b. Describe the role of encryption in securing an organization’s data and the ways that it can protect data exposed to risks in different states. (Google Documentation: Default encryption at rest)

c. Differentiate between authentication, authorization, and auditing. (Google Documentation: Authentication and authorization)

d. Describe the benefits of using two-step verification (2SV) and IAM. (Google Documentation: Identity and Access Management (IAM))

e. Describe how an organization can protect against network attacks using Google products, including distributed denial-of-service (DDoS) using Google Cloud Armor. (Google Documentation: Configure advanced network DDoS protection)

f. Define Security Operations (SecOps) in the cloud and describe its business benefits. (Google Documentation: Google Security Operations overview)

5.3 Google Cloud’s trust principles and compliance

● Describe how Google Cloud earns and maintains customer trust in the cloud. (Google Documentation: Creating trust through transparency)

a. Discuss how Google Cloud’s trust principles are a commitment to our shared responsibility for protecting and managing an organization’s data in the cloud. (Google Documentation: Creating trust through transparency)

b. Describe how sharing transparency reports and undergoing independent third-party audits support customer trust inGoogle.

c. Describe why data sovereignty and data residency may be requirements and how Google Cloud offers organizations the ability to control where their data is stored. (Google Documentation: Implement data residency and sovereignty requirements)

d. Describe how Google Cloud compliance resource center and Compliance Reports Manager support industry and regional compliance needs. (Google Documentation: Compliance Reports Manager)

Section 6: Scaling with Google Cloud Operations (~17% of the exam)

6.1 Financial governance and managing cloud costs

● Discuss how Google Cloud supports an organization’s financial governance and ability to control their cloud costs. (Google Documentation: Cost Management)

a. Discuss how using cloud financial governance best practices provides predictability and control for cloud resources.

b. Define important cloud cost-management terms and concepts.

c. Discuss the benefits of using the resource hierarchy to control access. (Google Documentation: Resource hierarchy)

d. Describe the benefit of controlling cloud consumption using resource quota policies and budget threshold rules. (Google Documentation: Create, edit, or delete budgets and budget alerts)

e. Discuss how organizations can visualize their cost data by using Cloud Billing Reports. (Google Documentation: View your billing reports and cost trends)

6.2 Operational excellence and reliability at scale

● Discuss the fundamental concepts of modern operations, reliability, and resilience in the cloud. (Google Documentation: Google Cloud Architecture Framework: Reliability)

a. Describe the benefits of modernizing operations by using Google Cloud.

b. Define important cloud operations terms.

c. Describe the importance of designing resilient, fault-tolerant, and scalable infrastructure and processes for high availability and disaster recovery. (Google Documentation: Architecting disaster recovery for cloud infrastructure outages)

d. Define key cloud reliability, DevOps, and SRE terms.

e. Describe how organizations benefit from using Google Cloud Customer Care to support their cloud adoption. (Google Documentation: Google Cloud Customer Care)

f. Describe the life of a support case during the Google Cloud Customer Care process. (Google Documentation: Customer Care procedures)

6.3 Sustainability with Google Cloud

● Discuss how Google Cloud helps organizations meet sustainability goals and reduce environmental impact. (Google Documentation: Cloud sustainability)

a. Describe Google Cloud’s commitment to sustainability and reducing environmental impact.

b. Discuss how Google Cloud provides products to support organizations’ sustainability goals.

2. Following the Google Cloud Digital Leader Learning Path

A cloud digital leader is able to explain the features of key cloud goods and services and how they help businesses. This free learning route leads you through a carefully chosen selection of on-demand courses, labs, and skill badges that provide you with practical, hands-on experience with Google Cloud technologies that are necessary for the Cloud Digital Leader job.

– Introduction to Digital Transformation with Google Cloud

https://www.cloudskillsboost.google/course_templates/266

Basic concepts including cloud, data, and digital transformation are define in this course. Additionally, it looks at real-world instances of firms embracing cloud computing to transform their industries. The course gives a broad overview of the possibilities and difficulties that businesses frequently face when they embark on a digital transformation path and connects them to the Google Cloud solution pillars. However, digital transformation involves more than merely utilizing new technologies. Organizations must be inventive and spread an innovation mentality throughout the whole organization if they are to undergo true transformation. For your benefit, the training provides best practices.

– Innovating with Data and Google Cloud

https://www.cloudskillsboost.google/course_templates/267

You’ll discover what data is, how businesses have historically utilized it to inform choices, and why it’s so important for machine learning in this course. Learners are also introduced to technical terms like organized and unstructured data, a data lake, a data warehouse, etc. The most popular and rapidly expanding Google Cloud data products are then covered.

– Infrastructure and Application Modernization with Google Cloud

https://www.cloudskillsboost.google/course_templates/265

This course examines the problems with an aging IT infrastructure and how companies might update it with cloud computing. Before moving on to application modernization and Application Programming Interfaces, it first examines the various cloud computing possibilities and their advantages (APIs). The course also discusses a variety of Google Cloud products including Compute Engine, App Engine, and Apigee that may aid organizations in better designing and managing their systems.

– Understanding Google Cloud Security and Operations

https://www.cloudskillsboost.google/course_templates/271

Cost control, security, and cloud operations are all topics cover in this course. It first examines how companies might opt to outsource their IT needs to a cloud provider in order to keep some or all of their own infrastructure. The next section covers Google Cloud’s defense-in-depth security and describes how the burden of data protection is divide between the organization and the cloud provider. Finally, it discusses the necessity for IT teams and business executives to reconsider IT resource management in the cloud as well as how Google Cloud resource monitoring tools may support them in keeping oversight and control over their cloud environment.

3. Expanding knowledge using Additional Training Resources

For certification exams like the Cloud Digital Leader Exam, the more learning materials you have available, the better the outcome. That is to say, you should concentrate on developing a more in-depth understanding of cloud services and products in order to have a successful revision. But there are a few sources worth looking into:

4. Complete your preparation using the Practice Tests

Imagine you’re taking the Google Cloud Digital Leader exam and you get a question about a certain subject. Then you were asked a question about an entirely unrelated subject. This could make you feel anxious during the exam. However, you’re undoubtedly prepare for the exam if you’re well-equipped to manage these circumstances. The best way to work on building this confidence is to start with the Professional Data Engineer practise examinations.

Taking practise tests is the most efficient way to gauge your level of preparedness. The Google Cloud Digital Leader Practice Exams can help you pinpoint your preparation’s weak points and lower your risk of making mistakes down the road. To ensure complete review, start taking full-length practise examinations after learning a subject.

Things to know after earning the certification:

In order to keep their certification status, you must recertify. All Google Cloud certificates are valid for two years from the date of certification, unless otherwise mentioned in the full-text descriptions. However, recertification is achieve by retaking the test and passing it during the recertification eligibility period.

Final Words

You must create and adhere to a study plan that covers all of the crucial material, includes practise exams, and enables you to advance your skills in order to pass the Google Cloud Digital Leader exam. Furthermore, you must concentrate on all of the crucial areas if you want to improve your preparedness. Start studying right away to ace the test.

Pulkit Dheer

With a background in Engineering and a great enthusiasm for writing, Pulkit focuses on intensive research to create targeted content. He brings his years of learning and experience to his current role. With a zeal towards technological research and powerful use of words dedicated to inspire and help professionals onset their career.

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