Google BigQuery Toolkit

Save time, empower your teams and effectively upgrade your processes with access to this practical Google BigQuery Toolkit and guide. Address common challenges with best-practice templates, step-by-step work plans and maturity diagnostics for any Google BigQuery related project.

Download the Toolkit and in Three Steps you will be guided from idea to implementation results.

The Toolkit contains the following practical and powerful enablers with new and updated Google BigQuery specific requirements:

STEP 1: Get your bearings

Start with...


• The latest quick edition of the Google BigQuery Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.


Organized in a data driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…


• Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation


Then find your goals...

STEP 2: Set concrete goals, tasks, dates and numbers you can track

Featuring 994 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Google BigQuery improvements can be made.

Examples; 10 of the 994 standard requirements:


1. How does BigQuery's GROUP BY clause work, and what are the different ways in which it can be used to group data, such as grouping by a single column, multiple columns, or even expressions? What are the implications of using the GROUP BY clause on large datasets, and are there any performance considerations that need to be taken into account?
   
   

2. How does BigQuery's window function feature enable aggregations over a set of table rows that are somehow related to the current row, such as aggregating over a partition or frame? What are some common use cases for using window functions, such as calculating running totals or averages, and how do they differ from traditional aggregations?
   
   

3. How can BigQuery's data summarization features be combined with other SQL features, such as subqueries and joins, to enable more complex data analysis and reporting? What are some common scenarios in which combining data summarization with other SQL features is particularly useful, and what are some best practices for doing so?
   
   

4. What are the different types of data summarization available in BigQuery beyond traditional aggregation and grouping, such as data sampling and data clustering? How do these techniques enable different types of data analysis, such as exploratory data analysis and data mining, and what are some common use cases for using them?
   
   

5. What are the different aggregation functions available in BigQuery, such as SUM, AVG, MAX, MIN, and COUNT, and how do they differ from one another in terms of their behavior and output? How do these functions handle NULL values, and are there any specific considerations that need to be taken into account when using them?
   
   

6. How can BigQuery's approximate aggregations, such as APPROX_COUNT_DISTINCT and APPROX_QUANTILES, be used to improve query performance when working with large datasets? What are the trade-offs associated with using approximate aggregations, and how do they differ from exact aggregations in terms of accuracy and precision?
   
   

7. Can BigQuery's query logs and access logs be used to trigger alerts or notifications in response to suspicious or anomalous activity, such as queries that exceed a certain threshold of data scanned or access attempts from unknown IP addresses, and how do these alerts help to enhance data security and compliance posture?
   
   

8. What are the different types of window frames available in BigQuery, such as ROWS, RANGE, and GROUPS, and how do they specify the set of rows over which a window function is computed? How do these frames enable different types of aggregations, such as aggregating over a fixed number of rows or a dynamic range of values?
   
   

9. What are the best practices for data visualization and storytelling with BigQuery GIS, including integration with data visualization tools such as Google Data Studio, Tableau, and Power BI, and how can these visualizations be used to communicate location-based insights effectively to stakeholders?
   
   

10. How does BigQuery's support for real-time data processing enable the creation of event-driven data pipelines that can respond quickly to changing business conditions, and what are the benefits of using BigQuery's streaming data processing capabilities for real-time analytics and decision-making?
    
    


Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:


• The workbook is the latest in-depth complete edition of the Google BigQuery book in PDF containing 994 requirements, which criteria correspond to the criteria in...


Your Google BigQuery self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:


• The Self-Assessment Excel Dashboard; with the Google BigQuery Self-Assessment and Scorecard you will develop a clear picture of which Google BigQuery areas need attention, which requirements you should focus on and who will be responsible for them:
  
  


• Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix

• Gives you a professional Dashboard to guide and perform a thorough Google BigQuery Self-Assessment

• Is secure: Ensures offline data protection of your Self-Assessment results

• Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:



STEP 3: Implement, Track, follow up and revise strategy

The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Google BigQuery projects with the 62 implementation resources:


• 62 step-by-step Google BigQuery Project Management Form Templates covering over 1500 Google BigQuery project requirements and success criteria:


Examples; 10 of the check box criteria:


1. Variance Analysis: Are indirect costs charged to the appropriate indirect pools and incurring organization?
   
   

2. Scope Management Plan: Is there any form of automated support for Issues Management?
   
   

3. WBS Dictionary: Does the contractors system provide unit or lot costs when applicable?
   
   

4. Risk Management Plan: Does the Google BigQuery project team have experience with the technology to be implemented?
   
   

5. Lessons Learned: How complete and timely were the materials you were provided to decide whether to proceed from one Google BigQuery project lifecycle phase to the next?
   
   

6. Risk Audit: Do you have position descriptions for all key paid and volunteer positions in your organization?
   
   

7. Quality Audit: What review processes are in place for your organizations major activities?
   
   

8. Requirements Management Plan: Did you avoid subjective, flowery or non-specific statements?
   
   

9. Initiating Process Group: Do you understand the quality and control criteria that must be achieved for successful Google BigQuery project completion?
   
   

10. Probability and Impact Assessment: What will be the likely political environment during the life of the Google BigQuery project?


 
Step-by-step and complete Google BigQuery Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:


• 1.1 Google BigQuery project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


• 2.1 Google BigQuery project Management Plan

• 2.2 Scope Management Plan

• 2.3 Requirements Management Plan

• 2.4 Requirements Documentation

• 2.5 Requirements Traceability Matrix

• 2.6 Google BigQuery project Scope Statement

• 2.7 Assumption and Constraint Log

• 2.8 Work Breakdown Structure

• 2.9 WBS Dictionary

• 2.10 Schedule Management Plan

• 2.11 Activity List

• 2.12 Activity Attributes

• 2.13 Milestone List

• 2.14 Network Diagram

• 2.15 Activity Resource Requirements

• 2.16 Resource Breakdown Structure

• 2.17 Activity Duration Estimates

• 2.18 Duration Estimating Worksheet

• 2.19 Google BigQuery project Schedule

• 2.20 Cost Management Plan

• 2.21 Activity Cost Estimates

• 2.22 Cost Estimating Worksheet

• 2.23 Cost Baseline

• 2.24 Quality Management Plan

• 2.25 Quality Metrics

• 2.26 Process Improvement Plan

• 2.27 Responsibility Assignment Matrix

• 2.28 Roles and Responsibilities

• 2.29 Human Resource Management Plan

• 2.30 Communications Management Plan

• 2.31 Risk Management Plan

• 2.32 Risk Register

• 2.33 Probability and Impact Assessment

• 2.34 Probability and Impact Matrix

• 2.35 Risk Data Sheet

• 2.36 Procurement Management Plan

• 2.37 Source Selection Criteria

• 2.38 Stakeholder Management Plan

• 2.39 Change Management Plan


3.0 Executing Process Group:


• 3.1 Team Member Status Report

• 3.2 Change Request

• 3.3 Change Log

• 3.4 Decision Log

• 3.5 Quality Audit

• 3.6 Team Directory

• 3.7 Team Operating Agreement

• 3.8 Team Performance Assessment

• 3.9 Team Member Performance Assessment

• 3.10 Issue Log


4.0 Monitoring and Controlling Process Group:


• 4.1 Google BigQuery project Performance Report

• 4.2 Variance Analysis

• 4.3 Earned Value Status

• 4.4 Risk Audit

• 4.5 Contractor Status Report

• 4.6 Formal Acceptance


5.0 Closing Process Group:


• 5.1 Procurement Audit

• 5.2 Contract Close-Out

• 5.3 Google BigQuery project or Phase Close-Out

• 5.4 Lessons Learned


Results

With this Three Step process you will have all the tools you need for any Google BigQuery project with this in-depth Google BigQuery Toolkit.

In using the Toolkit you will be better able to:


• Diagnose Google BigQuery projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices

• Implement evidence-based best practice strategies aligned with overall goals

• Integrate recent advances in Google BigQuery and put process design strategies into practice according to best practice guidelines


Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.

Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'

This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Google BigQuery investments work better.

This Google BigQuery All-Inclusive Toolkit enables You to be that person.

Includes lifetime updates

Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.