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From Data to Insights with Google Cloud Platform (DIGCP) Training
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Drive Team Excellence with From Data to Insights with Google Cloud Platform (DIGCP) Corporate Training

Data to Insights in Google Cloud Platform (GCP) transforms raw data into meaningful insights using various GCP services and tools. It involves multiple stages, including data collection, storage, processing, analysis, and visualization, to extract valuable insights to drive informed decision-making and business outcomes. Data-driven insights empower organizations to optimize operations, enhance customer experiences, and tailor products and services to meet evolving market demands. From Data to Insights with Google Cloud Platform (DIGCP) training empowers teams to make informed decisions, identify trends, predict outcomes, and drive strategic initiatives based on data-driven evidence.

Edstellar's From Data to Insights with Google Cloud Platform (DIGCP) instructor-led training course can be customized to meet organization's requirements. The virtual/onsite From Data to Insights with Google Cloud Platform (DIGCP) training course, led by expert trainers, offers interactive sessions that combine practical, hands-on learning experiences with theoretical knowledge.

Get Customized Expert-led Training for Your Teams
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Scale Your Training: Small to Large Teams
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Experience Hands-On Learning from Industry Experts
Delivery Capability Across 100+ Countries & 10+ Languages
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Skills Your Employees Will Gain

These are the core, hands-on capabilities your team builds during the program.

  • Data Analysis
    Data Analysis is the process of inspecting, cleansing, and modeling data to discover useful information. This skill is important for roles like data scientist and business analyst, as it drives informed decision-making and strategy development.
  • Storage Solutions
    Storage Solutions involve designing and managing efficient data storage systems. This skill is important for IT professionals to ensure data accessibility, security, and scalability.
  • Pipeline Design
    Pipeline Design involves creating efficient systems for transporting fluids, gases, or solids. this skill is important for engineers and project managers to ensure safety, efficiency, and compliance.
  • Data Visualization
    Data Visualization is the ability to represent data graphically, making complex information accessible and understandable. this skill is important for analysts and decision-makers to identify trends, insights, and patterns effectively.
  • Querying Techniques
    Querying Techniques involve using structured languages like SQL to extract and manipulate data from databases. This skill is important for data analysts and developers to derive insights and support decision-making.
  • Machine Learning
    Machine Learning is the ability to develop algorithms that enable computers to learn from data. This skill is important for data scientists and AI engineers to create predictive models and enhance automation.

What Your Team Will Achieve After This Training

  • Analyze large datasets using Google Cloud Platform tools to extract meaningful insights
  • Evaluate data storage options and choose the most suitable solution for specific business needs
  • Design and implement data pipelines for efficient data ingestion and processing
  • Create interactive data visualizations to communicate insights effectively to stakeholders
  • Apply advanced querying techniques to extract valuable information from structured and unstructured data
  • Develop machine learning models to predict future trends and patterns from historical data
  • Optimize data processing workflows for improved performance and cost-effectiveness
  • Collaborate with cross-functional teams to leverage data-driven decision-making processes

Topics & Program Outline

The curriculum is organized into focused modules built by industry experts and delivered virtually or on-premise. Interactive sessions reflect the evolving demands of the workplace, keeping the learning both relevant and practical.

  1. Overview of Google Cloud platform
    • Definition and components
    • Key advantages and features
  2. Introduction to Big Data
    • Understanding Big Data concepts
    • Characteristics and challenges
  3. Data storage options on Google Cloud
    • Google Cloud Storage (GCS) for object storage
    • Google Cloud SQL for relational database storage
    • Google Bigtable for NoSQL database storage
  4. Introduction to Google Cloud storage
    • Use cases and applications
    • Features and benefits
  5. Introduction to Google Cloud bigtable
    • Overview and architecture
    • Use cases and best practices
  6. Introduction to Google Cloud datastore
    • Features and capabilities
    • Use cases and deployment scenarios
  7. Introduction to Google BigQuery
    • Overview and core functionality
    • Key features and benefits
  1. Overview of Big Data Tools on Google Cloud
    • Understanding the Big Data ecosystem
    • Introduction to key tools and services
  2. Introduction to Apache Hadoop and Spark on Google Cloud
    • Overview of Apache Hadoop
    • Introduction to Apache Spark
    • Use cases and practical applications
  3. Introduction to Dataflow
    • Introduction to Dataflow
    • Understanding stream and batch processing
    • Hands-on examples and demonstrations
  4. Introduction to Dataproc
    • Overview of Google Cloud Dataproc
    • Use cases and deployment scenarios
    • Managing and scaling clusters on Dataproc
  1. Introduction to SQL
    • What is SQL?
    • Basic syntax
  2. Basic SQL queries
    • SELECT statement
    • WHERE clause
    • ORDER BY clause
  3. Advanced SQL queries
    • JOINS
    • Subqueries
  4. Working with views and stored procedures
    • Creating and managing views
    • Creating and managing stored procedures
  1. Understanding BigQuery pricing model
    • On-demand pricing
    • Flat-rate pricing
  2. Cost optimization strategies
    • Query optimization
    • Data storage optimization
  1. Data cleaning techniques
    • Removing duplicates
    • Handling missing values
    • Standardizing data formats
  2. Data transformation with SQL
    • Using SQL functions for transformation
    • Creating derived columns
  3. Data Transformation with Dataflow
    • Overview of Dataflow
    • Writing Dataflow pipelines for transformation
  1. Storing data on Google Cloud storage
    • Uploading data to Cloud storage
    • Managing data in Cloud storage
  2. Exporting Data from BigQuery
    • Exporting query results to Cloud Storage
    • Exporting tables to Cloud Storage
  1. Batch data ingestion
    • Loading data from Cloud storage
    • Loading data from other Google Cloud services
  2. Real-time data ingestion
    • Streaming data into BigQuery
    • Using Dataflow for real-time ingestion
  1. Introduction to Data Visualization
    • Importance of data visualization
    • Types of visualizations
  2. Visualization tools on Google Cloud
    • Overview of Data Studio
    • Overview of Looker
  3. Creating dashboards with Data Studio
    • Building reports
    • Creating interactive dashboards
  1. Joining datasets in BigQuery
    • Inner joins
    • Outer joins
    • Cross joins
  2. Merging Datasets with Dataflow
    • Using CoGroupByKey
    • Merging multiple datasets
  1. Advanced SQL functions
    • Aggregate functions 
    • Window functions
  2. Advanced SQL clauses
    • GROUP BY
    • HAVING
    • PARTITION BY
  1. Schema Design best practices
    • Choosing the right data types
    • Normalization vs. denormalization
  2. Working with Nested Data in BigQuery
    • Arrays and structs
    • Querying nested data
  1. Advanced Visualization techniques
    • Advanced chart types
    • Geo maps and time series
  2. Creating interactive reports
    • Adding interactivity to reports
    • Using parameters and filters
  1. Performance optimization techniques
    • Query optimization tips
    • Indexing strategies
  2. Query Performance Optimization
    • Analyzing query execution plans
    • Using query cache and slot reservations
  1. Access control in BigQuery
    • IAM roles and permissions
    • Dataset-level and table-level permissions
  2. Securing data on Google Cloud platform
    • Encryption at rest and in transit
    • Data masking and redaction techniques
  1. Introduction to Notebooks
    • Overview of Cloud-based notebooks
    • Use cases for notebooks in data analysis
  2. Using Notebooks for data analysis
    • Exploratory data analysis
    • Data visualization in notebooks
  1. Overview of Machine Learning on Google Cloud
    • Introduction to TensorFlow
    • Introduction to AI platform
  1. Introduction to BigQuery Machine Learning (BQML)
    • Overview of BQML
    • Use cases for BQML
  2. Building Machine Learning Models with BQML
    • Linear regression
    • Logistic regression
    • Model evaluation and deployment

Who Should Attend?

This program suits professionals at many levels across the organization, including:

  • Data Analysts
  • Data Scientists
  • Cloud Engineers
  • Data Engineers
  • Business Analysts
  • Software Developers
  • System Architects
  • Technical Support Engineers
  • IT Administrators
  • Database Administrators
  • DevOps Engineers
  • Managers

What are the Prerequisites?

Professionals with basic proficiency with ANSI SQLcan take up the From Data to Insights with Google Cloud Platform (DIGCP) training course.

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We design training your teams actually engage with, and deliver it the way that suits you best. Through a vetted global trainer network, Edstellar runs sessions in 10+ languages with consistent quality anywhere.

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Virtual From Data to Insights with Google Cloud Platform (DIGCP) Training

Virtual / online: expert-led live sessions delivered anywhere, with consistency and easy scheduling.

We deliver anywhere worldwide
Standardized content for consistent outcomes
Join from own workspace, no travel
We scale to large groups across sites
Interactive tools keep remote learners engaged
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On-site From Data to Insights with Google Cloud Platform (DIGCP) Training

On-site (in-house): immersive, instructor-led learning at your office.

Our trainers run face-to-face at your office
We tailor setup/content to your workplace and tools
Group exercises drive collaboration
Live demos +  hands-on practice
Direct trainer access to clarify doubts
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Off-site From Data to Insights with Google Cloud Platform (DIGCP) Training

Off-site: focused, instructor-led group learning away from everyday workplace distractions.

We host your teams at a venue of your preferred choice
Built-in group activities for bonding
Full uninterrupted schedule for focus/retention
Boosts morale and signals commitment
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        What Sets Edstellar Apart

        Experienced Trainers

        Our trainers are drawn from a vetted global network and bring years of industry expertise, keeping every session practical and impactful.

        Proven Quality

        With a strong global track record, Edstellar is known for quality and engaging delivery.

        Industry-Relevant Curriculum

        Our programs are built by experts to match the demands of today's industry.

        Fully Customizable

        Every program can be tailored to your organization's goals.

        Comprehensive Support

        We provide pre- and post-session support for a complete learning experience.

        Global Multi-Location & Multilingual Training Delivery

        We deliver in multiple languages to support diverse global teams.

        Recognition That Motivates Your Team

        Upon successful completion of the training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

        This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

        Recognition That Motivates Your Team
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