Majority of Consumer Goods Shoppers in the U.S. will Not Compromise on Brand Principles: Google Commissioned Research
3081
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
Editor’s note: This article first appeared in Consumer Goods Technology Magazine
Shifting work habits, more online shopping options, rising inflation, and stretched supply chains are just a few factors making it harder to discern what’s top-of-mind for shoppers today.
But we’re starting to get a clearer picture of what consumers say they value most right now. New Harris Poll research commissioned by Google Cloud reveals how U.S. shoppers are thinking about consumer goods brands in new ways—from apparel, electronics, and beauty products, to food and beverage.
While price unsurprisingly continues to be a major consideration in purchases, the average shopper is increasingly paying close attention to the values of consumer goods brands and how eco-friendly their products and practices are.
Shoppers want to buy from brands aligned with their values
COVID-19 drove people to reflect on their priorities, elevating concepts like community service, equity, and sustainability. A decade ago, most consumer goods companies would not have made these front-and-center, operational priorities. But today’s consumer not only wants savings and convenience, they also want that good feeling that comes from spending their money with a company that aligns with their values.
Our new research reveals that 82% of shoppers prefer a consumer brand’s values to align with their own, and they’ll vote with their wallet if they don’t feel a match. Three-quarters of shoppers reported parting ways with a brand over a conflict in values.
Even with their favorite consumer goods products, a majority of shoppers will not compromise on principles. If there’s a value mismatch, 39% of shoppers said they’d permanently boycott their favorite brand, and 24% would break ties at least temporarily. Most won’t be quiet about their concerns either: 28% of consumers that found their values at odds with a brand said they have shared their concerns with friends and family, and another 15% have shared their qualms on social media.
Consumer goods companies need to prioritize sustainability
A majority of today’s consumers (52%) are especially interested in supporting sustainable brands. They want to know how companies are managing their resources, specifically whether they are sourcing responsibly. These shoppers want to see meaningful, measurable efforts from CPG firms to save energy and reduce waste, like how Nuuly, URBN’s digital rental and resale business, has woven sustainability into its business operations, from its distribution centers to reusable packaging.
In fact, 66% of shoppers are now seeking out eco-friendly brands, with 55% saying they would pay more for more sustainable products. But these same shoppers are skeptical too: 72% think that companies and brands overstate their sustainability efforts. And they’re right to question brands’ practical application of their values. According to another Harris Poll survey recently commissioned by Google Cloud, 58% of executives polled across 16 countries admit that their organization has overstated its sustainability efforts.
Product availability is table stakes
A final point from the research: The global supply chain has stretched past its limits, and 60% of consumers are voicing some level of concern about it. At the end of the day, if a preferred brand isn’t actually on the shelves of a real or digital store, it doesn’t matter what the brand’s values or sustainability efforts are. A staggering 98% said they’d either buy from a different brand or search other stores or websites.
What’s a brand to do?
After more than 25 years working in the consumer goods industry in roles ranging from marketing and product development to business strategy and technology, at companies like Johnson & Johnson, Kimberly Clark, Carter’s, and now Google Cloud, I’ve seen successful brands do four things well when it comes to their values:
- Don’t be generic.
Your brand’s values need to be authentic, and they need to have teeth. But being too bold could run the risk of alienating some consumer segments. This is where technology can help. Personalizing your messages and outreach to specific shopper profiles is one way to ensure that your core values reach the right customers at the right time. - Make your values clear and consistent.
When focusing on which values to highlight with your consumers and the world, make sure they make sense for your brand and that you’ll stick to them over time. For example, it’s painfully obvious when a brand is being opportunistic and inserting itself into conversations around values like sustainability or social justice, when it doesn’t have a history of voicing those values. The key to clear and consistent messaging of values is balancing authenticity with relatability and the appropriate amount of promotion. - Develop sustainability practices and communicate their impact to everyday people.
How everyday people perceive a consumer goods brand’s sustainability initiatives is different from how an investor or general business audience does. Shoppers don’t read business sustainability plans or impact reports. To increase awareness of your brand’s sustainability efforts, consumers need to identify and interact with your brand and products directly. Some of my favorite examples are how I love that Google Maps gives me the choice of eco-friendly driving directions, and that I know I can buy low-waste, packaging-free cosmetics from a company like Lush. - Reward customer loyalty.
Shoppers have more choices than ever before, and supply chain woes are testing preferences even further. But when someone chooses a specific brand because they feel aligned with their values or like their eco-friendly products, that shopper doesn’t always get recognized or thanked. Implementing a rewards program or following-up with customers after their purchases is one way you can make loyal shoppers feel appreciated while creating a lasting relationship that extends as long as possible.
3815
Of your peers have already downloaded this article
4:30 Minutes
The most insightful time you'll spend today!
Moving to the cloud offers enormous benefits for businesses. Yet there are risks as well. The challenge is multidimensional, with far reaching implications not just for the solutions that will run in the cloud, but also for the technologies that support them, the people who need to implement them, and the processes that govern them.
The rubric of people, process, and technology is a familiar one. But how do you harness it to move forward?
The Google Cloud Adoption Framework builds a structure on the rubric of people, process, and technology that you can work with, providing a solid assessment of where you are in your journey to the cloud and actionable programs that get you to where you want to be. It’s informed by Google’s own evolution in the cloud and many years of experience helping customers.
You can use the framework yourself to make an assessment of your organization’s readiness for the cloud and what you’ll need to do to fill in the gaps and develop new competencies.This framework can help you find your way, from your first project all the way to becoming a cloud-first organization.
2022 is a Big Year for the Gaming Industry!
3852
Of your peers have already read this article.
2:00 Minutes
The most insightful time you'll spend today!
Editor’s note: This post was originally published in TechPulse Belgium, where Jack Buser, Google Cloud’s Director of Game Industry Solutions, shared his trends for the industry this year.
The year 2022 will hold many surprises (with a few already dropping!), but there’s one near certainty: By this time next year there will be millions more gamers worldwide. It’s thanks to the industry’s little-noted technology growth drivers, which are getting stronger.
Games are no longer a niche hobby; it’s global, mainstream entertainment. There were 3.1 billion gamers worldwide in 2020. It’s estimated that by 2024 there will be another 500 million. With a global population of 7.7 billion, that’s nearly half the planet. Revenues in 2021 may reach $175 billion—likely more than movies, music, and books combined.
It’s a strength unique to the games industry, driven by the way its creators deploy new technology. Advances we see in everything from pricing and emerging markets, to backend computing and delivery suggests it will grow from here, on things like artificial intelligence and planet-scale networks.
Games forever, game better
It’s no surprise that videogames have become a huge business. Playing games is one of our deepest human expressions. There is a 4,500 year old board game that people still play, a testimony to the human love of testing cleverness, honing reactions, building trust, or just enlivening a day.
Video games do all that and for decades game makers have taken the most cutting-edge computing tech to make things better. We’ve seen electronic ping pong become shooting asteroids, to simple (yet iconic) 2D sprites evolve into believable, expressive 3D characters, all leading to today’s immersive worlds hosting tens of millions of players worldwide.
There’s more to come. I work at technology’s cutting edge for games, offering the world’s leading game creators access to powerful cloud computing, a low-latency global network, Machine Learning and AI, and much more. As usual, game innovators are taking up all these tools, building new narratives, new ways to play, new markets, and new jaw-dropping moments.
And game creators aren’t just thinking about players; they’re also thinking about viewers. More and more people are watching eSports, and creators are using the games medium to engage their viewers in increasingly immersive ways.
Streaming like never before
AI and ML are sharpening games and attracting new players in other ways. These technologies increasingly power everything from network performance to global player matching. The delicate but essential work of encouraging newcomers and discouraging bad actors, optimizing monetization, or building and scaling up new player environments.
Another important area we’re seeing cloud tools being put to use is in coordinating the workflows of global teams of developers. It’s not just a question of building faster anymore, but of collaborating and responding more effectively. The distributed work trends that featured so strongly during the pandemic had already featured in much of the game industry, increasingly it’s an industry standard. This will likely mean even faster and more diverse game development, addressing the needs of new markets where we’re seeing double-digit growth.
Tools like cloud streaming, 5G, and edge computing are likely to accelerate the use of Game Streaming, Augmented Reality, and other types of immersive gameplay. If my metaverse doesn’t have games, count me out! We’re looking at some exciting new developments in coming months with some major industry players. Stay tuned.
A big year for the games industry
As a premier provider of solutions, tools and services to games companies, our engineering job is complex and global. Fortunately, our mission is simple: Help game companies transform to meet new global opportunities with planet scale solutions. Technology has brought the gaming industry to astonishing heights, and is the perfect compliment to great storytelling and creative ingenuity.
As a decades-long industry veteran, I’ve never been more impressed with what technology can do for our industry. Looking past 2022, when we’ll see more compute, more AI, more AR, and more innovation around healthy and exciting game play, there is just one near certainty: More growth.
Hike: Processing Analytics Queries 20X Faster with Google Cloud Platform
5566
Of your peers have already read this article.
2:30 Minutes
The most insightful time you'll spend today!
After a seamless migration to Google Cloud Platform with CloudCover and Google Cloud Professional Services, Hike has reduced its costs by 20% and processed analytics queries 20 times faster than with its previous cloud provider. The business is also using AI and machine learning to enhance the experience provided by a new sticker-based messaging app, Hike Sticker Chat.
India is a market of opportunity for businesses that provide messaging apps to consumers. With more than 1.3 billion people, the country is the second most populous in the world. However, global messaging app providers face a robust market challenge from Hike, a home-grown internet and technology startup. Launched in 2012, Hike provides innovative products such as Hike Messenger and more recently the AI- and machine-learning-enabled Hike Sticker Chat, a service that enables young people in the country to express themselves through digital stickers.
The business says it understands the people of India and communication like no one else, while its mission is to reduce individuals’ dependency on the keyboard. To do this, Hike is building one of the largest repositories of AI and machine-learning-enabled stickers for Hike Sticker Chat. This messaging platform is, according to Hike, the only product of its type that enables conversations through stickers covering more than 40 languages and local dialects.
Google Cloud Results
- Processes analytics queries 20X faster than previously
- Doubles compute throughput
- Uses Google Cloud Machine Learning Engine managed, distributed capabilities to train complex models on TensorFlow that provide delightful local sticker recommendations through Hike Sticker Chat
Founded by Kavin Bharti Mittal, the Delhi-based venture is backed by SoftBank, Tencent, Tiger Global, Foxconn, and Bharti. To date, Hike has raised $261 million in funding. In August 2016, Hike raised its Series D round of funding, led by Tencent and Foxconn, at a valuation of $1.4 billion. The business is one of the fastest Indian startups to achieve Unicorn status, doing so in less than four years.
Hike started operations on a multinational cloud service. However, as user numbers and usage grew, the business began exploring options to improve performance and stability, reduce costs, and cut administration loads. In particular, Hike wanted to reduce latency between cloud data centers.
Focus on product development
“We aimed to move away from a technology stack with single points of failure to a horizontally scaled, highly reliable, distributed systems and managed services environment that enabled us to focus on product development rather than operations,” says Aditya Gupta, Director, Engineering, Hike.
Hike then began exploring the opportunities presented by Google Cloud Platform. The business held a number of executive-level meetings with Google to understand the capabilities, roadmap, and track record of the cloud service. It then decided to proceed with a proof of concept with Google Cloud Premier Partner CloudCover.
The proof of concept revealed that when Cloud Load Balancing was operating, latency between the Google Cloud data center in Taiwan and Delhi, India, was less than the latency between the incumbent cloud provider’s data center and Delhi. Further, compute throughput was up to two times greater on Compute Engine than on the equivalent service, while Hike could complete more then 1 million connections on Compute Engine – up from 500,000 connections on the incumbent service.
Migrate to GCP
The success of the exercise prompted Hike to migrate its messaging app to Google Cloud Platform. “We chose Google Cloud Platform because of its very broad set of services and features,” explains Gupta. “In addition, Google’s innovation mindset and the richness of the partnership would allow us to be onboarded quickly to machine learning services such as Cloud Machine Learning Engine.”
The business called on Google Cloud Professional Services (Technical Account Management) to help ensure a seamless lift-and-shift migration over two months. Google Cloud Professional Services initially undertook a technical infrastructure kickoff to establish a foundation for architecture requirements such as identity and access management and security.
Google Cloud Professional Services team delivers smooth migration
Google Cloud Professional Services worked closely with Hike to map out and deliver the Google Cloud Platform architecture that would deliver the greatest value to the business. The Professional Services team also worked with Hike to resolve product and support queries quickly; provided project background for product and support teams; and organized project meetings and early adopter program access.
In addition, Professional Services team members worked on site at least once a week, coordinated external support during critical migration periods, and coordinated teams in five countries for a single, 17-hour migration marathon. Over 60 days, the business migrated 7,000 processor cores, running virtual machine instances used for messaging infrastructure and analytics, to Google Cloud Platform.
Throughout the exercise, Google Cloud Professional Services worked with CloudCover to educate the customers’ technology teams to achieve proficiency with Google Cloud Platform. The teams soon built up skills and knowledge of best practices and began applying them to the Google Cloud Platform environment.
The Hike Google Cloud Platform architecture comprises virtual machine instances running in Compute Engine; Cloud Storage for unified object storage; networking; a BigQuery analytics data warehouse; Cloud Dataflow to transform and enrich data; Cloud Load Balancing to distribute workloads to maximize efficiency; and Cloud Dataproc to run Hadoop clusters.
Hike is also stepping up its AI & machine learning capabilities. It uses Google Cloud Machine Learning Engine managed, distributed computing capabilities to train complex models on TensorFlow. This powers key use cases such as delightful local sticker recommendations on Hike Sticker Chat. Hike is also investing heavily on AI and machine learning research.
Hike has achieved a range of benefits from its Google Cloud Platform deployment. As well as reduced latency, improved compute throughput, and increased connection handling, Google Cloud Platform managed services have enabled the business to reduce the time and effort required to administer core infrastructure, with the saved resources allocated to improving its messaging product.
“Managed services are beginning to reduce our operational overheads,” says Gupta. “For example, managed instance groups and Cloud Load Balancing are reducing our instance count and costs, thereby reducing involvement from DevOps and developer teams.”
Google Cloud Platform 20% cheaper
Gupta and his team have calculated that running for three years on Google Cloud Platform will cost, including the cost of migration, 20 percent less than on its previous platform. BigQuery is processing queries 20 times faster than a similar service offered by the previous provider, while storing 125TB of data and streaming 1.5TB of data daily. Furthermore, Hike’s analytics pipeline costs 80 percent less than in its previous environment.
“Google Cloud Platform has played an important role in enabling us to continue to innovate and realize our mission of reducing dependency on the keyboard,” says Gupta.
Google Cloud’s Data Analytics May Recap
6895
Of your peers have already read this article.
5:00 Minutes
The most insightful time you'll spend today!
May was a very busy month for data analytics product innovation. If you didn’t have the chance to attend our inaugural Data Cloud Summit, video replays of all our sessions are now available so feel free to watch them at your own pace.
In this blog, I’d like to share some background behind the innovations we released in May, why we built them the way we did, and the type of value they can bring your company and your team.
But first, a huge thank you!
This week, we had the honor to announce that Google has been named a Leader in The Forrester Wave™: Streaming Analytics, Q2 2021 report. Forrester gave Dataflow a score of 5 out of 5 across 12 different criteria, stating: “Google Cloud Dataflow has strengths in data sequencing, advanced analytics, performance, and high-availability”.
Google has more than a decade of experience in building real-time and internet-scale systems for its own needs, and we are excited to see that our ability to provide customers with a reliable, scalable, and performant platform is bearing fruit.
This announcement comes on the back of the release of The Forrester Wave™: Cloud Data Warehouse, Q1 2021 report, which also named Google Cloud as a Leader.
We couldn’t be more excited about the recognition and appreciate all your feedback and trust in the work that we do to support your goal in accelerating data-powered innovation.
Innovation galore
Your feedback and your passion is the fuel that drives our ambition to deliver more and better services to you. That’s why, this year, we didn’t want to wait until Google Cloud Next to share some great products we have been working on. On May 26, our team announced a slew of new products, services and programs. Watch a quick summary below:
https://youtube.com/watch?v=DG1mOPMXJvw%3Fenablejsapi%3D1%26
Meeting you where you are
An important design principle behind all of our services is “meeting you where you are”. This means we aim to provide you with the tools and software you need to innovate on your own terms. Here are three new services that will help you do just that:
Datastream
Datastream, our new serverless change data capture (CDC) and replication service, allows your company to synchronize data across heterogeneous databases, storage systems, and applications reliably and with minimal latency to support real-time analytics, database replication, and event-driven architectures. Datastream delivers change streams from Oracle and MySQL databases into Google Cloud services such as BigQuery, Cloud SQL, Cloud Storage, and Cloud Spanner, saving time and resources while ensuring your data is accurate and up-to-date.
- Under the hood, Datastream reads CDC events (inserts, updates, and deletes) from source databases, and writes those events with minimal latency to a data destination. It leverages the fact that each database source has its own CDC log—binlog for MySQL and LogMiner for Oracle—which it uses for its own internal replication and consistency purposes.
- Datastream integrates with purpose-built and extensible Dataflow templates to pull the change streams written to Cloud Storage, and create up-to-date replicated tables in BigQuery for analytics. It also leverages Dataflow templates to replicate and synchronize databases into Cloud SQL or Cloud Spanner for database migrations and hybrid cloud configurations.
- Datastream also powers a Google-native Oracle connector in Cloud Data Fusion’s new replication feature for easy ETL/ELT pipelining. By delivering change streams directly into Cloud Storage, customers can leverage Datastream to implement modern, event-driven architectures.
Looker and BigQuery Omni on Microsoft Azure
Research on multi cloud adoption is unequivocal — 92% of businesses in 2021 report having a multi cloud strategy. We want to continue supporting your choice by providing the flexibility you need to see your strategy through.
- This past month, we introduced Looker, hosted on Microsoft Azure. For the first time, you can now choose Azure, Google Cloud, or AWS for your Looker instance. You can also self-host your Looker instance on-premises.
- We also introduced BigQuery Omni for Azure, which along with last year’s introduction of BigQuery Omni for AWS, will help you access and securely analyze data across Google Cloud, AWS, and Azure.
The cost of moving data between cloud providers isn’t sustainable for many, and it’s still difficult to seamlessly work across clouds. BigQuery Omni represents a new way of analyzing data stored in multiple public clouds, which is made possible by BigQuery’s separation of compute and storage. By decoupling these two, BigQuery provides scalable storage that can reside in Google Cloud or other public clouds, and stateless resilient compute that executes standard SQL queries.
- Unlike competitors, BigQuery Omni doesn’t require you to move or copy your data from one public cloud to another, where you might incur egress costs. You also benefit from the same BigQuery interface on Google Cloud, enabling you to query data stored in Google Cloud, AWS, and Azure without any cross-cloud movement or copies of data.
- BigQuery Omni’s query engine runs the necessary compute on clusters in the same region where your data resides. For example, you can query Google Analytics 360 Ads data stored in Google Cloud and query logs data from your ecommerce platform and applications that are stored in AWS S3 and/or Microsoft Azure.
Then, using Looker, you can build a dashboard that allows you to visualize your audience behavior and purchases alongside your advertising spend.
Dataplex
We understand that most organizations still struggle to make high-quality data easily discoverable and accessible for analytics, across multiple silos, to a growing number of people and tools within their organization.
They are often forced to make tradeoffs. For instance, moving and duplicating data across silos to enable diverse analytics use cases or leaving their data distributed but limiting the agility of decisions.
- Dataplex provides an intelligent data fabric that enables you to centrally manage, monitor, and govern your data across data lakes, data warehouses, and data marts, while also ensuring data is securely accessible to a variety of analytics and data science tools.
- One of the core tenets of Dataplex is letting you organize and manage your data in a way that makes sense for your business, without data movement or duplication. For that, we provide logical constructs like lakes, data zones, and assets. These constructs enable you to abstract away the underlying storage systems and become the foundation for setting policies around data access, security, lifecycle management, and so on.
- For example, you can create a lake per department within your organization (e.g. Retail, Sales, Finance, etc.) and create data zones that map to data readiness and usage (e.g. landing, raw, curated_data_analytics, curated_data_science, etc.).
Once you have your lakes and zones setup, you can attach data to these zones as assets. You can add data from different types of storage (e.g. GCS Bucket and BigQuery dataset) under the same zone. You can also attach data across multiple projects under the same zone. You can ingest data into your lakes and zones using the tools of your choice, including services such as Dataflow, Data Fusion, Dataproc, Pub/Sub, or choose from one of our partner products. Dataplex comes with built-in 1-click templates for common data management tasks.
To find out more about Dataplex, head to cloud.google.com/dataplex or watch the video below:
https://youtube.com/watch?v=bbFeAt7cw1g%3Fenablejsapi%3D1%26
Helping you innovate everyday
Sharing data is hard. Traditional data sharing techniques use batch data pipelines that are expensive to run, create late arriving data, and can break with any changes to the source data. These techniques also create multiple copies of data, which brings unnecessary costs and can bypass data governance processes. They also fail to offer features for data monetization, such as managing subscriptions and entitlements. Altogether, these challenges mean that organizations are unable to realize the full potential of transforming their business with shared data.
Analytics Hub
To address these limitations, we are introducing Analytics Hub, a new fully managed service that helps organizations unlock the value of data sharing, leading to new insights and increased business value.
This new service is built on the tremendous experience and feedback we have received over the years. For example, BigQuery has had cross-organizational, in-place data sharing capabilities since its inception in 2010—and the functionality is very popular. Over a 7-day period in April, we had over 3,000 different organizations sharing over 200 petabytes of data. These numbers don’t include data sharing between departments within the same organization.
Analytics Hub takes sharing to the next level, making it easy for you to publish, discover, and subscribe to valuable datasets that you can combine with your own data to derive unique insights.
This includes:
- Shared datasets: As a data publisher, you create shared datasets that contain the views of data that you want to deliver to your subscribers. Data subscribers can search through the datasets that are available across all exchanges for which they have access and subscribe to relevant datasets. In addition, the publisher can track subscribers, disable subscriptions, and see aggregated usage information for the shared data.
- Curated, self-service data exchanges: Exchanges are collections used to organize and secure shared datasets. By default, exchanges are completely private, but granular roles and permissions make it easy to deliver data to the right audience—whether internal or public.
This is just the beginning for Analytics Hub. Please sign up for the preview, which is scheduled to be available in the third quarter of 2021.
Dataflow Prime
At Google Cloud, we have the great privilege of working with some of the most innovative organizations in the world. And this work provides us with a unique perspective into the future of big data processing. Dataflow Prime is a new platform based on a serverless, no-ops, and auto-tuning architecture that brings unparalleled resource utilization and radical operational simplicity to big data processing. This new service introduces a large number of exciting capabilities but I’d like to highlight three key aspects of the product:
- Vertical Autoscaling: Dataflow Prime dynamically adjusts the compute capacity allocated to each worker based on utilization, detecting when jobs are limited by worker resources and automatically adding more resources. Vertical Autoscaling works hand in hand with Horizontal Autoscaling to seamlessly scale workers to best fit the needs of the pipeline. As a result, it no longer takes hours or days to determine the perfect worker configuration to maximize utilization.
- Right Fitting: Each stage of a pipeline typically has a different resource requirement than the others. Until now, either all workers in the pipeline would have had the higher memory and GPU, or none of them would. Pipelines either had to waste resources or suffer slower workloads. Right Fitting solves this problem by creating stage-specific pools of resources, optimized for each stage.
- Smart Recommendations: Smart Recommendations automatically detects problems in your pipeline and shows potential fixes. For example, if your pipeline is running into permissions issues, a Smart Recommendation will detect which IAM permissions you need to enable to unblock your job. If you are using an inefficient coder in your job, Smart Recommendations will surface more performant coder implementations that can help you save on costs.
What’s next
We’re excited to hear your thoughts and feedback about all these exciting new services. I would also highly recommend that you connect with members of the community to learn more about their story and journey. A good example to start with is the Data To Value customer panel we produced at our inaugural Data Cloud Summit with the Chief Data Officers of Keybank and Rackspace. You can watch it for free below:
https://youtube.com/watch?v=ITI2Q3MkxuA%3Fenablejsapi%3D1%26
HarbourBridge Schema Assistant Allows Quick, Bulk Migration to Cloud Spanner
5457
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
Today we’re announcing the HarbourBridge Schema Assistant, which provides a guided schema-design workflow for migrating from MySQL or PostgreSQL to Spanner. HarbourBridge imports dump files (from mysqldump or pg_dump) or directly connects to your source database, and converts the source database schema to an equivalent Spanner schema. The new Schema Assistant capability displays the source schema and Spanner schema side-by-side, highlights errors and walks you through a series of steps to validate and optimize your Spanner schema. It also produces a browsable assessment report with an overall migration-fitness score for Spanner, a table-by-table detailed analysis of type mappings and a list of features used in the source database that aren’t supported by Spanner. It supports editing of table and column names, column types, primary keys and constraints, as well as dropping of tables, columns, foreign keys and secondary indexes.
The new Schema Assistant complements HarbourBridge’s existing data and schema migration capabilities and is a critical step towards our goal of building a complete open-source migration toolkit. HarbourBridge continues to support command-line schema and data migration and turn-key Spanner evaluation.
Complementing the bulk data migration capabilities of HarbourBridge, we are also announcing the ability to migrate change events from MySQL to Cloud Spanner.
Supported Features in Schema Assistant
- Global type mapping. Users can customize the global mapping for how types should be mapped to Spanner consistently across the schema. For example, mapping large integers in source schema to Spanner’s NUMERIC.
- Local type mapping. Users can override the custom type mapping for a given table/column.
- Session management. A session keeps track of all the changes made to the schema mapping.
- Customization of secondary indexes. Users can add, edit and delete secondary indexes to optimize their Spanner performance.
- Customization of foreign keys and interleaved tables. Table interleaving is an important design consideration when migrating to Cloud Spanner as explained in more detail in this blog post.
Features in the pipeline
We are already working to further expand the supported set of schema editing features and welcome your feedback. We are particularly excited to expand the Schema Assistant’s design recommendations for optimizing Spanner schemas e.g. in-depth recommendations for primary key design.
HarbourBridge is open source and we gladly accept contributions from the wider community.
More Relevant Stories for Your Company
Google Cloud Accelerates Financial Organizations’ Journey towards Digital Transformation
When I reflect back on the past year and the pandemic, I’m struck by how the reliance on remote work and operations has changed the fundamentals of business forever. For the financial services industry, this rings particularly true. Many conversations I’m having right now with organizations revolve around embracing a transformation
8 Must-Have Google Cloud Products for Startups
Startups worldwide turn to Google Cloud tools to build fast on a strong and easy to use platform that helps them get to market and launch products faster, all while building on the cleanest cloud in the industry. Startups leverage Google Cloud and our Google for Startups Cloud Program to
Beany’s Cloud-Based Accounting Solutions Transform Small Business Finance
Many people start a small business that aligns with their passions, but soon discover the day-to-day running of a business is very different than anticipated. Dealing with accounting, finance, and other daily activities can quickly overwhelm even the most promising of new businesses. Recognizing the unique challenges facing small businesses,
Microservices: An Application Architecture Optimized for the Cloud
The need for agility and flexibility in the face of accelerating innovation and disruptions from competitors is the primary driver for cloud adoption across businesses both big and small. However, simply moving and shifting legacy system to the cloud does not sufficiently meet enterprise needs. The systems and applications running
