3200
Of your peers have already watched this video.
20:30 Minutes
The most insightful time you'll spend today!
Delivering analysis-ready financial data at scale
Refinitiv, is a leading provider of financial market data. It serves over 40,000 institutions and operates in 190 countries.
“We’re constantly looking at solving some of the most difficult problems our users face when accessing new data sets as well as onboarding new sources that will be relevant for workflows across the front, middle, and back office,” says Catalina Vazquez, Proposition Director, Tick History, Refinitiv.
For every dollar spent on financial market data, a further eight are spent in processing, storing, and transforming that data before it can be analyzed. That’s a problem Refinitiv wanted to get at.
Refinitiv partnered with Google Cloud to deliver instant access to 25 years of financial markets data. What was formerly delivered by hard disk then managed by hand is now provided automatically with BigQuery.
Watch Tom Salmon, Customer Engineer, Google Cloud and Catalina Vazquez and learn how Refinitiv addressed key challenges by designing their architecture with Google Cloud’s simplicity, security, scale, and speed in mind.
11229
Of your peers have already watched this video.
1:30 Minutes
The most insightful time you'll spend today!
Indian Retailer Figures Optimizes Hyperlocal Delivery to Increase Customer Experience
Anyone who follows the Indian e-commerce scene knows that one of the largest challenges these companies face is hyperlocal delivery.
That was a problem facing Wellness Forever, a retail chain of pharmacies with 150-plus stores across India.
“Exactly a year ago, we started our journey of hyperlocal deliveries. This optimization was a big time challenge for us to understand how to optimize this,” Palani Subbiah, CTO, Wellness Forever.
The problem in front of Wellness Forever was to identify which customer could can be sold from which store, so that a delivery could be made within 90 minutes.
“We handle a large amount of customer data and we wanted to use insights to help and improve the customer satisfaction index,” says Subbiah.
To do that Wellness Forever leveraged Google Big Query to run massive amount of data to come up with the operational insights. They also used Firebase and Google Maps.
“By 2021, we are going to have about 450 stores. Those stores are going to be not only a physical store, which is a digital store.

Upgrade Your Contact Center with Knowlarity’s AI-powered Speech Analytics for Higher CX
DOWNLOAD E-BOOK6218
Of your peers have already downloaded this article
7:00 Minutes
The most insightful time you'll spend today!
Did you know, everyday about 56 million hours worth of phone conversations, equalling to 420 billion spoken words are handled by contact centers? Knowlarity, a renowned cloud business communication service provider with nearly 6,000 customers and over a million virtual users, leverages AI-powered speech analytics that offer insights to gauge customer preferences and emotions, campaign performance, agent’s effectiveness and much more. Knowlarity’s programmatic speech analytics platform is built with Google Cloud to optimize contact center performance by transcribing and analyzing millions of calls to impact savings, operations, CX, customer loyalty and retention, and revenue generation.
Download the e-Book to learn more about Knowlarity’s speech analytics for your business’ contact centers and elevate your agents’ performance by leveraging ML, natural language processing (NLP) and AI capabilities.
How Google Cloud & NGIS’ Partnership Powers Sustainability & Responsible Sourcing for Consumer Brands

6202
Of your peers have already read this article.
2:00 Minutes
The most insightful time you'll spend today!
In the competitive world of consumer goods, sustainability matters more than ever. In recent Google survey, 82% of consumers said sustainability is more top of mind now than it was before COVID-191 and 78% said that big businesses have a role to play in helping to fight climate change.2 As well as delivering on customers’ heightened expectations, sustainable business practices can help organizations reduce waste and lower operational costs and even help attract top talent.
Not only is sustainability good for business performance and the bottom line, it’s great for the planet, too. And it’s something we care deeply about at Google. Since our earliest days, we have focused on developing services that significantly improve the lives of billions of people while operating our business in an environmentally sustainable way. In 2007, we were the first major company to become carbon neutral, and in 2017 we were the first to achieve 100% renewable energy. Today, we proudly operate the cleanest cloud in the industry. We’ve also been powering humanitarian, scientific, and environmental initiatives studying geospatial information and making it available for analysis via Google Earth Engine.
Powering the future of responsible sourcing
How does all this relate to CPG supply chains? The world relies on raw materials like palm oil, soy, and cocoa to produce the items we consume every day—such as coffee, chocolate, frozen foods, shampoo, toothpaste, cosmetics, and even household cleaning products. Yet as demand for these materials continues to grow, forests are under threat. Change is needed.
As sustainability moves further into the spotlight, in-demand crops face increased supplier scrutiny. Environmentally conscious companies want to know what percentage of their raw materials is sourced from deforestation-free suppliers—and how they can improve that number. Until recently, many CPG brands have found it hard to get real-time, reliable visibility into operations at a local supplier level, globally.
Google Cloud, in partnership with NGIS, is helping brands gain a deeper understanding of raw material sourcing practices across supplier networks, so they can improve supplier performance and compliance in the fight against deforestation. The TraceMark solution, developed by NGIS, uses Google Earth Engine and BigQuery to analyze and visualize how suppliers behave over time.
Google Earth Engine is the world’s largest archive of open Earth data. It combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities to help people detect changes, map trends, and quantify differences on the Earth’s surface.With Earth Engine, organizations can analyze the potential social, and environmental impacts of the decision they make.
Together, TraceMark, Google Earth Engine and BigQuery help companies visualize, monitor, and measure the impact of suppliers’ farming practices. The process starts with Earth Engine, which aggregates and harmonizes planetary data into images that it has been collecting for decades. Then, boundary maps for different suppliers are created and NGIS applies climate data science and machine learning to turn pixels into insights. Finally, BigQuery and Vertex AI -Google Cloud’s unified artificial intelligence platform are used to produce supplier scoring, which is integrated into downstream ERP and procurement systems to support more informed decision-making.
These efforts support the responsible sourcing of raw materials by making supply chains more agile, transparent and traceable.

“NGIS is thrilled to work with Google Cloud and its partners to enable business accountability for sustainable practices at all levels of their supply chain,” said Nathan Eaton, Executive Director, NGIS. “Google Earth Engine provides unique geospatial capability that [gives] leaders visibility and control over their environmental footprint and that of their suppliers in a way that was not previously possible.”
Unilever commits to working towards a deforestation-free supply chain
Unilever is a great example of a company committed to using technology in the quest to become more sustainable. Since 2020, Unilever has partnered with Google Cloud to use data for eco-friendly decision-making, particularly when it comes to sustainable commodity sourcing.
By combining the power of cloud computing with satellite imagery and AI, we’re helping Unilever build a more holistic view of the forests, water cycles, and biodiversity that intersect its supply chain. By gaining a complete picture of these ecosystems, Unilever can detect deforestation while simultaneously prioritizing critical areas of forest and habitats in need of protection.
The cleanest cloud for your sustainable transformation
We are excited to bring Google Earth Engine and NGIS to our CPG customers to help them meet their sustainability goals. Looking ahead, we’re committed to furthering our own ambitious sustainability goals and empowering CPG brands with the technology to do more for our environment and our shared future.
Contact your cloud seller to learn more about Tracemark sustainable sourcing solutions and how Google Cloud can help you advance your sustainability initiatives.
Explore TraceMark on the Google Cloud Marketplace
To know more about how we are helping CPGs transform digitally read this ebook
1. Google/C Space, BR, FR, DE, IN, MX, U.K., U.S., qualitative survey activity, n = 528, Nov. 24–Nov. 26, 2020.
2. Google/Ipsos, Google Sustainability, BR, FR, DE, IN, JP, U.K., U.S., n=16,959 online population 18–70, July 2021.
Bit Capital Rolls Out a Digital Financial Solution in Under 3 Months and at 2/3 the Cost

5682
Of your peers have already read this article.
4:00 Minutes
The most insightful time you'll spend today!
In the past few years, a series of new technologies and regulatory changes has been transforming Brazil’s financial industry. The concept of blockchain added security and agility to financial transactions. The open banking system being deployed by the country’s Central Bank (BC) allows for platform integration and data sharing -with the user’s consent- between financial institutions. Recently, the launch of Pix, also by the BC, has shaken the market by creating a new payment method that is instant, free for individuals and 24/7.
Since 2018, the startup Bit Capital has been working on the development of 100%-digital financial solutions in the cloud to help its clients adapt to this new scenario in a convenient way, without the need to build an infrastructure for that or hiring different providers. Pix was not the exception.
In less than 3 months, the team was able to build and go live with a solution that can be used by both direct participants (i.e. those with banking licenses granted by BC) and indirect participants (i.e. companies depending on direct participants to offer payments on Pix) through Bit Capital’s platform.
Besides this differential, Pix and the startup’s other solutions are based on blockchain and Google Cloud’s cloud, ensuring greater security, scalability and availability for customers and allowing for an easy integration between Bit Capital’s platform’s solutions and those from other companies.
“Now we have a platform with an API and various microsservices, allowing clients to connect and develop their own financial product without having to start from scratch.”
—Francesco Miolo, CFO, Bit Capital
A robust structure to handle Pix’s high demand
Bit Capital was established with a certain urgency to develop its platform. The idea was well-developed and customers were interested. The fast deployment of Google Cloud’s tools was one of the main factors that attracted the company to use it as a basis for its infrastructure.
“We managed to deliver everything we have today in Google Cloud with a small team. That was another challenge: being able to grow with a few people,” says Juliano Souza, the startup’s head of IT infrastructure. “We sought other cloud partners, but they had a steep curve. We chose Google Cloud because we needed quick, quality scaling.”
The same thing happened when they built the solution for Pix, despite the specific challenges involved. The BC had performance requirements that led the company to spend some time experimenting until they reached the best suite of tools to meet those requirements. The startup wanted to create a unique architecture that could help both large and small customers and be integrated to the platform’s other microservices.
With the support from Google Cloud’s team to answer doubts and make the best decisions, the solution was built in a few months, at a cost about two-thirds lower than other providers.
The solution’s architecture is based on apps running in Docker in Google Kubernetes Engine (GKE), with interconnected microservices. The blockchain system runs on Compute Engine, its rows are managed in Pub/Sub and Dataflow, and persistent data, in Cloud SQL. Cloud Interconnect is used for the connection with BC. Cloud KMS and Secrets Management store the company’s pre-credentials. All of this is supported by Cloud Load Balancing for load balancing and autoscaling.
According to the team, GKE was essential for the solution’s success. Using infrastructure as code in the tool made uploading of a group of microservices significantly easier. Developers are able to help set up this environment, which has helped spread the DevOps culture in the team. Besides orchestrating and integrating apps, GKE also provides an elastic structure to handle demand peaks and visibility to monitor internal components.
“Google Kubernetes Engine was the only way to ensure availability, observability and elasticity for all clients, whether small, middle-sized or large.”
—Juliano Souza, Head of IT Infrastructure, Bit Capital
Nowadays, the solution’s environment has 20 clusters with over 1,500 pods – 250GB in data per month, providing a robust structure to support a service involving periods of intense demand such as Black Friday.
Ease to monitor, fix and improve
Just 10 days after Pix’s official launch date, the company had its first test: Black Friday. This allowed a major e-commerce customer to test the scale and see the success of the architecture that had been built. “It worked great regarding what the cloud could deliver. And we found what we needed to fix very quickly. Operations [formerly Stackdriver], in particular Cloud Trace, showed us clearly what needed to be done to improve performance,” Souza explains.
Using Operations added reliability by putting deliveries into production. Checking Cloud Trace to see if there were any performance issues and the exact point where they were happening became routine for Bit Capital’s developers. Google Cloud’s security tools and Google Safety Center provided the resources needed to monitor and secure the environment, with automatic data encryption at rest and in transit.
“Google Cloud has security as a premise. When we upload any kind of component, like a database or a virtual machine, the drive is encrypted by default. With other providers, you must specify that you want it encrypted.
”—Juliano Souza, Head of IT Infrastructure, Bit Capital
The easy service monitoring and management accelerates product and technology development because the team no longer needs to worry about infrastructure. Automated management allows professionals to spend more time on new projects and the company’s business. Also, the deployment of services in a Google Cloud multi-region impacts on customer experience, providing high availability for their solutions.
In the coming months, Bit Capital aims to ramp up service usage and the creation of new projects in Google Cloud by adding more customers to Pix’s solution and Banking as a Service (BaaS) solutions. Anthos will be incorporated to the tool suite to make it easier to connect apps with the customers’ on-prem environments. And the deployment of open banking has the potential to be a business driver for the company.
“We joke that we’re already doing open banking, because we have various connections with different providers, which allows us to offer an integrated solution,” says Francesco Miolo, the startup’s CFO. “With the arrival of the new regulations, something we are waiting for since we started out, we will be able, through our platform, to take our customers to the open finance ecosystem, enabling the development of disruptive business models.”

4978
Of your peers have already downloaded this article
2:35 Minutes
The most insightful time you'll spend today!
One of the toughest challenges for data scientists, and big data engineers is gathering, preparing, and transforming data, and creating data pipelines.
Gathering data for a machine learning or big data initiative can be hard work. The mere act of getting it all together can leave data teams so excited that they can overlook critical safeguards. The result? You could have data that’s skewed, or biased, or data sets that are too small to generate accurate models.
This is why it’s important to have a pre-ML data checklist. A pre-machine-learning data checklist will ensure you have the right data sets for your models, thereby improving your chances of success.
Here are some other benefits:
You waste less time: A checklist allows you to save the time you would normally spend trying to work through your own mental checklist.
Fewer errors: A pre-ML data checklist ensures you have don’t overlook obvious mistakes, and have relevant, unbiased, and representative data.
Lower cognitive load: By using a checklist, you remove the burden of unnecessary cognitive load. This enables you to free up the brain power required for more productive tasks such as model selection and tuning.
More Relevant Stories for Your Company

Data-first Digitization Helps Leverage the Cloud for Your Mainframe Assets
For many enterprises, the venerable mainframe is home to decades’ worth of data about the company’s customers, processes and operations. And it goes without saying that the business would like access to that mainframe data — to report on it, to analyze it with big data analysis tools, or to

What’s New in Retail: Bits from Google Cloud’s Retail & Consumer Goods Summit
Today we’re hosting our Retail & Consumer Goods Summit, a digital event dedicated to helping leading retailers and brands digitally transform their business. For me, this is a personally exciting moment, as I see tremendous opportunities for those companies that choose to focus on their customers and leverage technology to elevate

DocAI Lowers Customer’s Document Processing Cost by 60 Percent. Learn How
Some of the most important data at your company isn’t living in databases, but in documents, and most business processes begin, involve or end with a document. Yet most companies are still manually entering data and reliant on guesswork to make sense of it all as the volume and variety

Setting up Data Pipelines Easily for Streaming and Non-Streaming Data
We live in a world of incessant data. Our phones, factory equipment, smart watches, health devices, and other IoT devices are constantly streaming data. Some of the most popular uses of machine learning and AI are also based on streaming data. Think real-time credit card fraud detection, or software that






