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Vishakha Lohar

Member since 2023

Gold League

93569 points
Empower Gen AI apps with tool use Earned Jun 19, 2025 EDT
Data Warehousing for Partners: Analyze Data with Looker Earned Jun 18, 2025 EDT
Developing Data Models with LookML Earned Jun 18, 2025 EDT
Accelerate Knowledge Exchange with Gemini Enterprise Earned Jun 17, 2025 EDT
Get Started with Looker Earned Jun 13, 2025 EDT
Analyzing and Visualizing Data in Looker Earned Jun 11, 2025 EDT
Data Migration Tool Earned Jun 6, 2025 EDT
Visualize Your Data in Looker Earned Jun 2, 2025 EDT
BI Reporting: Looker Visualization on BigQuery Earned Jun 2, 2025 EDT
Delivery Shadowing Earned Jun 2, 2025 EDT
Case Studies Earned May 29, 2025 EDT
Technology + Beyond the UI Earned May 29, 2025 EDT
Technology + Within the UI Earned May 29, 2025 EDT
Table Calculations, Pivots, and Visualizations Earned May 29, 2025 EDT
Building Reports in Looker Earned May 29, 2025 EDT
Liquid Templates and Parameters Earned May 29, 2025 EDT
Extends to Keep LookML DRY Earned May 29, 2025 EDT
Admin Roles and Folder Access Earned May 29, 2025 EDT
Version Control and Caching Earned May 27, 2025 EDT
The Modern Data Platform and LookML Earned May 27, 2025 EDT
Driving Data Culture and Designing Dashboards Earned May 26, 2025 EDT
Gen AI Agents: Transform Your Organization Earned May 20, 2025 EDT
Gen AI Apps: Transform Your Work Earned May 20, 2025 EDT
Gen AI: Navigate the Landscape Earned May 19, 2025 EDT
Gen AI: Unlock Foundational Concepts Earned May 19, 2025 EDT
Gen AI: Beyond the Chatbot Earned May 19, 2025 EDT
Data Warehousing for Partners: Process Data with Dataflow Earned Jan 29, 2025 EST
Google Cloud Fundamentals: Core Infrastructure Earned Oct 23, 2024 EDT
Build and Deploy a Generative AI solution using a RAG framework Earned Jul 11, 2024 EDT
Prompt Design in Vertex AI Earned Jul 9, 2024 EDT
Cloudera to Google Cloud Earned Jul 4, 2024 EDT
Cloud Healthcare API Earned Mar 14, 2024 EDT
Data Warehousing for Partners: Enable Google Cloud Customers Earned Nov 22, 2023 EST
Data Lake Modernization on Google Cloud: Cloud Composer Earned Nov 21, 2023 EST
Achieving Business Outcomes with Looker Earned Nov 6, 2023 EST
Looker Explained Earned Nov 3, 2023 EDT
Cloud Engineering Earned Oct 31, 2023 EDT
Prepare Data for Looker Dashboards and Reports Earned Oct 31, 2023 EDT
Manage Data Models in Looker Earned Oct 30, 2023 EDT
Implementing Generative AI with Vertex AI Earned Sep 24, 2023 EDT
Generative AI Fundamentals Earned Sep 24, 2023 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned Sep 24, 2023 EDT
Generative AI Fundamentals Earned Sep 24, 2023 EDT
Introduction to Responsible AI Earned Sep 22, 2023 EDT
Introduction to Large Language Models Earned Sep 22, 2023 EDT
Introduction to Generative AI Earned Sep 21, 2023 EDT
Understanding LookML in Looker Earned Aug 21, 2023 EDT
Applying Advanced LookML Concepts in Looker Earned Aug 14, 2023 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI Earned Jun 30, 2023 EDT
DEPRECATED BigQuery for Marketing Analysts Earned Jun 29, 2023 EDT
Document AI Earned Jun 29, 2023 EDT

An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.

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This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.

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This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

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Unite Google’s expertise in search and AI with Gemini Enterprise, a powerful tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Gemini Enterprise assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.

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In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with migrating from an Enterprise Data Warehouse (EDW) to BigQuery using the DMT tool and sample data. Learners will complete a lab that uses the DMT tool to transfer schema and data from Teradata to BigQuery.

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This skill badge course aims to unlock the power of data visualization and business intelligence reporting with Looker, and gain hands-on experience through labs.

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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.

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In this course, you shadow a series of client meetings led by a Looker Professional Services Consultant.

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By the end of this course, you should feel confident employing technical concepts to fulfill business requirements and be familiar with common complex design patterns.

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In this course you will discover additional tools for your toolbox for working with complex deployments, building robust solutions, and delivering even more value.

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Develop technical skills beyond LookML along with basic administration for optimizing Looker instances

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This course reviews the processes for creating table calculations, pivots and visualizations

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This course is designed for Looker users who want to create their own ad-hoc reports. It assumes experience of everything covered in our Get Started with Looker course (logging in, finding Looks & dashboards, adjusting filters, and sending data)

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In this course you will discover Liquid, the templating language invented by Shopify and explore how it can be used in Looker to create dynamic links, content, formatting, and more.

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Hands on course covering the main uses of extends and the three primary LookML objects extends are used on as well as some advanced usage of extends.

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This course is designed to teach you about roles, permission sets and model sets. These are areas that are used together to manage what users can do and what they can see in Looker.

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This course aims to introduce you to the basic concepts of Git: what it is and how it's used in Looker. You will also develop an in-depth knowledge of the caching process on the Looker platform, such as why they are used and why they work

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This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.

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This course provides an iterative approach to plan, build, launch, and grow a modern, scalable, mature analytics ecosystem and data culture in an organization that consistently achieves established business outcomes. Users will also learn how to design and build a useful, easy-to-use dashboard in Looker. It assumes experience with everything covered in our Getting Started with Looker and Building Reports in Looker courses.

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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape s the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataflow.

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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.

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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from five products hosted on Cloudera or Hortonworks to corresponding Google Cloud services and hosted products. The migration solutions addressed will be: HDFS data to Google Cloud Dataproc and Cloud Storage Hive data to Cloud Dataproc and the Cloud Dataproc Metastore Hive data to Google Cloud BigQuery Impala data to Google Cloud BigQuery HBase to Google Cloud Bigtable Sample data will be used during all five migrations. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.

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Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-based data formats and protocols of existing healthcare technologies, Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including streaming data processing with Cloud Dataflow, scalable analytics with BigQuery, and machine learning with Cloud Machine Learning Engine. In this Quest you will use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets.

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This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.

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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.

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In this course, we’ll show you how organizations are aligning their BI strategy to most effectively achieve business outcomes with Looker. We'll follow four iterative steps: Plan, Build, Launch, Grow, and provide resources to take into your own services delivery to build Looker with the goal of achieving business outcomes.

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By the end of this course, you should be able to articulate Looker's value propositions and what makes it different from other analytics tools in the market. You should also be able to explain how Looker works, and explain the standard components of successful service delivery.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.

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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.

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This course will help ML Engineers, Developers, and Data Scientists implement Large Language Models for Generative AI use cases with Vertex AI. The first two modules of this course contain links to videos and prerequisite course materials that will build your knowledge foundation in Generative AI. Please do not skip these modules. The advanced modules in this course assume you have completed these earlier modules.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.

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In this course, you will get hands-on experience applying advanced LookML concepts in Looker. You will learn how to use Liquid to customize and create dynamic dimensions and measures, create dynamic SQL derived tables and customized native derived tables, and use extends to modularize your LookML code.

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Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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This course provides partners the skills required to scope, design and deploy Document AI solutions for enterprise customers utilizing use-cases from both the procurement and lending arenas.

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