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Submission: On April 17 via manual from HK — Scanned from DE
Submission: On April 17 via manual from HK — Scanned from DE
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CONGRATULATIONS TO THE 2023 APAC INNOVATION AWARD WINNERS
Sahir Azam
March 30, 2023 | Updated: April 4, 2023
#Events
I’m thrilled to announce the nine winners of the 2023 MongoDB APAC Innovation
Awards. The MongoDB Innovation Awards honor projects and people who dream big.
They celebrate the groundbreaking use of data to build compelling applications
and the creativity of professionals expanding the limits of technology with
MongoDB. This year, we have broken the awards down regionally to celebrate
organizations in APAC, from startups to industry-leading enterprises, across a
wide variety of industries, who are delivering big results. We are delighted to
announce the winners below:
2023 MONGODB APAC INNOVATION AWARD WINNERS:
POSITIVE IMPACT
OPEN GOVERNMENT PRODUCTS
Open Government Products (OGP) is an in-house team of engineers, designers, and
product managers, who is a part of the Singapore Government, and is responsible
for building technologies for the public good. OGP used MongoDB’s developer data
platform, MongoDB Atlas to create its digital form builder, FormSG. Used by the
Singapore government and public healthcare institutions, FormSG securely
collects data from residents and businesses and helps public officers to create
digital government forms in minutes. It eliminates the use of paper forms and
the manual process of transcribing physical documents, which had raised concerns
around data privacy and protection. During the pandemic, FormSG enabled public
officers to collect more than 100,000 daily temperature declarations nationwide.
Today, FormSG has served more than 120,000 public officers from 155 agencies and
it has created more than 500,000 digital forms to help the government collect
data on travel and health declarations by visitors to the country, applications
for COVID-19 swab tests, and applications for financial assistance.
ORGANIZATION TRANSFORMATION
BENDIGO AND ADELAIDE BANK
Bendigo and Adelaide Bank is one of Australia’s largest banks, with around 7,000
employees helping more than 2.2 million customers achieve their financial goals.
The bank has been on a multi-year journey of transformation using MongoDB's
developer data platform to improve efficiency and deliver a better customer
experience as they fulfill their vision to become Australia’s bank of choice.
Recently, the cloud team launched Ready-Set-MongoDB (or RSM). This event-driven
framework allows developers to streamline the consumption of internal or
external APIs, and applies data transformations and storage automatically within
a MongoDB collection of their choice. Using MongoDB Atlas Search, the bank also
enabled developers to gain insights across its multi-cloud deployments,
identifying cost savings, and providing inventory information to account owners
and technical stakeholders.
Within the first 18 months of launching these programmes, the automation had
saved the organization more than 1,100 developers days. It also helped reduce
human involvement, removed stale data, and allowed engineers to focus on the
things that matter. The development of Ready-Set-MongoDB is ongoing and
improving, as new Bendigo multi-cloud challenges arise and new MongoDB products
are released. The application is a perfect representation of how Bendigo's
Technology Department is using modern technology, rapid development, and
innovation-led problem solving to drive organizational transformation.
HEROES IN HEALTH
REDCLIFFE LIFETECH PRIVATE LIMITED
Over the last few years, Redcliffe Labs has become India's fastest growing
technology-driven diagnostics service provider. Redcliffe Labs is on a mission
to serve 500 Million Indians by 2030 with fusion of technology and world- class
laboratories. The company already serves thousands of people daily, with more
than 73 labs and close to 1500 walk-in centers across 180 cities.
Redcliffe Labs has relied on MongoDB Atlas’ flexible document model to power its
innovative Smart Health Report, a patient resource that provides a number of
indicators and trackers to gauge holistic health. The MongoDB developer data
platform's best in class security, compliance, and privacy controls allows
Redcliffe's team to confidently handle even the most sensitive patient data.
MongoDB Atlas takes care of many of the traditional database management
challenges, which means that developers can spend their time building
diagnostics for patients, rather than managing databases. Redcliffe Labs is
focusing on incorporating next-generation technologies in the diagnostics space
with an AI platform that will make Interactive Diagnostics reports, Advanced
Health Profiling and more detailed Diagnostics and Health Alerts.
INDUSTRY DISRUPTOR
CATHAY PACIFIC
Cathay Pacific, Hong Kong’s home carrier operating in more than 60 destinations
worldwide, has been on an impressive journey to become one of the very first
airlines to create a truly paperless flight deck. Until recently, a flight from
Hong Kong to New York would require a crew to review more than 150 pages of
finely printed text and charts before their flight and make ongoing updates
throughout the trip.
In 2019, Cathay Pacific conducted the first zero paper flight, removing 50kg of
manuals, charts, maps, and flight briefing paperwork. They achieved this
enormous feat with the help of one seamless and highly customized iPad
application: Flight Folder. Built on MongoDB Atlas, Flight Folder is designed to
improve the pilot briefing experience. MongoDB helped consolidate dozens of
different information sources into one place, and made it possible for flight
crews to easily share their experiences with others. It also included a digital
refueling feature that helps crews become much more efficient with fueling
strategies – saving significant flight time and costs. The use of MongoDB Device
Sync enables seamless syncing and no data loss even when the app goes on- and
offline mid-flight.
Since the Flight Folder launch, Cathay Pacific has completed more than 340,000
flights with full digital integration in the flight deck. In addition to the
greatly improved flight crew experience, flight times have been reduced, and
digital refueling saves eight minutes of ground time on average. All these
efficiencies have helped the company avoid the release of 15,000 tons of carbon.
FROM BATCH TO REAL-TIME
ADANI DIGITAL LABS
Adani Digital Labs is the India-based digital innovation arm of the larger Adani
group. The lab’s team's mission is to create one single platform – a SuperApp
called AdaniOne – to empower a billion stories in India.
To address several use cases and the huge scale that will be required by the
superapp, the Adani Digital team selected MongoDB Atlas as its the main
transactional database that will further enhance the application.
A key component of the app is how it can bring together disparate data in order
to provide a single view of activity across the application. In the first
process, developers had taken out the data in batches and sent it to their
database However, this was too slow and unpredictable as far as business
requirements are concerned. Also, the consolidated view of customer history,
orders, inventory, and supply chain network updates was likely to impact their
customer's ability to generate revenue.
Therefore, in order to find a better solution, Adani Digital Labs built a more
modern architecture in line with MongoDB. Using MongoDB's Change Streams and the
data platform's native Kafka connector, they created an event-based architecture
that pushes the data out in real-time for analysis. Adani Digital Labs is still
in the early phases of the SuperApp's rollout and collaborating with MongoDB as
its developer data platform continues to help the firm to grow and deliver
insights in real time.
INDUSTRY 4.0
DONGWHA
Founded in 1948, the Dongwha Group has evolved from a singular focus on the wood
and timber industry into a global leader across a number of sectors including
building materials, chemicals and media.
As part of its wider digital transformation strategy, Dongwha required smarter
factories that would improve and optimize their production efficiency. Dongwha
built an innovative Smart Factory Software platform that collects and analyzes
data to enhance quality and production management capabilities.
Originally, the platform was built with the community version of MongoDB.
However, in order to scale and adapt, the team recently migrated to MongoDB
Atlas in the cloud. This enabled them to store large volumes in the fastest and
most secure way, optimize their solution for time series data, and make it easy
to run machine learning across their data.
Dongwha completed the migration seamlessly, without any disruption or downtime
to their factories, and it has now been launched across five different sites.
Over the last year, the application has significantly increased its availability
and reliability while performance has improved by as much as 6x . As they look
to the future, Dongwha plans to roll out the software to more of its
international factories.
DIGITAL NATIVE
MYBILLBOOK
India is home to more than 60 million small and medium-sized businesses (SMBs)
but only a small portion of those SMBs are taking advantage of digitization and
many still operate using pen and paper. In addition, many businesses in India
still struggle with fluctuations in internet services, outages, and latency.
FloBiz is on a mission to change that with myBillBook, a one-stop solution that
helps SMBs create professional invoices, manage stock, collect payments,
automate reminders through smart banking, engage with their customers, manage
staff attendance and payroll and generate more than 25 business reports for
accounting and decision making. The app is also mobile-first, so businesses can
access them from their mobile devices and allows users to manage billing and
inventory in both online and offline environments.
The myBillbook app is powered by MongoDB Atlas, providing the flexible and
scalable foundation for the business to do everything from building new features
to performing complex analytical queries. In addition, Realm, MongoDB’s mobile
database, with Atlas Device Sync, supports offline usage and automatic syncing
with the cloud to ensure there is never data or functionality loss for users due
to poor internet connection. Because of its success in supporting customers with
business critical operations, more than 6.5 million business owners in India are
now using myBillbook for their billing, accounting, collection and business
growth.
CUSTOMER FOCUSED
KASIKORN BUSINESS-TECHNOLOGY GROUP
Established in 1945, Kasikornbank (KBank) is one of the largest and oldest banks
in Thailand. Their mission is to strive towards service excellence and empower
every customer’s life and business. One of KBank’s subsidiaries, KASIKORN
Business-Technology Group (KBTG), developed a mobile banking application – MAKE
by KBank. MongoDB Atlas’ flexibility and ease of development enabled MAKE’s
development team to choose the best type of database for its tasks, to automate
data tiering with Atlas Online Archive, and to reduce hours spent on operational
maintenance. With more time to focus on delivering new innovations to customers,
they created unique features like Cloud Pocket which can allocate funds into
unlimited customizable pockets for separate usage. They also built Pop Pay, a
feature that allows users to easily search for nearby friends and transfer money
by clicking their profile picture as well as “Expense Summary" a spending
analysis services that helps inform and manage users’ financial habits. As of
January 2023, MAKE has acquired more than 1 million users, and increased the
number of transactions in MAKE from 900,000 to more than 7.5 million in a span
of one year.
MASSIVE SCALE
CHINA MOBILE
China Mobile provides mobile voice and multimedia services via its nationwide
mobile telecommunications network across mainland China and Hong Kong. It is the
world's largest mobile network operator by total number of subscribers.
The telecommunications leader is using MongoDB to support one of its largest and
most critical push services, which sends out billing details to more than 1
billion users every month. Prior to MongoDB, the tech team relied on Oracle, but
as the user numbers increased, performance degraded. Despite large investments,
it was still taking too long to do basic requests like finalize and deliver
bills to users. In 2019, after comprehensive testing, China Mobile migrated to
MongoDB. By taking advantage of MongoDB's native sharding, they were able to
improve performance by 80% and go from 50 Oracle machines, to just 12 machines
for the same workload. The service now handles all current requirements and is
set up to scale with future growth.
With the support of MongoDB, China Mobile is growing steadily,with more than 168
million monthly users and has one of the highest customer satisfaction scores in
the China Mobile group.
← Previous
THREE WAYS RETAILERS USE SEARCH BEYOND THE ECOMMERCE STORE
When consumers think of retail search, the first thing that comes to mind is
typically the search bar of an ecommerce website. This is for a good reason: a
Salesforce commerce study shows that 87% of shoppers begin their shopping
journey in the search bar, and Forrester has found that as many as 68% of
shoppers would not return to a site that provided a poor experience. But
retailers that exclusively focus on search capabilities in the context of
ecommerce are missing out on huge benefits in customer experience and workforce
efficiency. To drive fast application experiences, the querying and indexing of
data sets is vitally important, and can be a game changer for easy performance
optimization. Let’s explore some of the innovative ways that retailers are using
search indexes to super-power their application experiences. Why search is
important across retail organizations Large retail data sets, like product and
customer data, are used by both customer-facing ecommerce or loyalty
applications and internal use cases: inventory management, stock management,
customer care, purchasing, supplier and vendor management, marketing and more.
Customers using ecommerce search bars typically have an excellent “Google-like”
experience with auto-complete, faceting, fuzzy matching, etc., but the retail
workforce and back office staff often aren't given the same luxury. These
internal teams are trying to work efficiently, but they are stuck using front
ends powered by a traditional operational database with no search indexing
capabilities. These teams are missing out on a search engine that is optimized
for unknown or unpredictable workloads. Search indexing will speed up queries
where the input is user-defined or might be searching across multiple fields.
Let’s look at a comparison: FIgure 1: Database Query vs. Search Query For these
under-served and often overlooked use cases, retailers need a quick and
cost-effective solution to adding search, like MongoDB Atlas Search. Adding a
search index to an application can be done in minutes, without creating
operational complexity. MongoDB manages the spin up and management of the
backend Apache Lucene search engine, and the complex data and index
synchronization activity. Figure 2: MongoDB Atlas: Integrated database and
search The three most common use cases for retail The easy addition of search
can optimize application performance and usability in the retail industry in
three important areas: In-store workforce applications Back office inventory and
assortment Customer servicing Figure 3: Example Search use cases in three retail
industry areas In-store workforce applications Speed is important in workforce
applications, because these interactions happen in real time. Think of an
in-store customer spelling out a name in full at checkout for a grocery purchase
to be added to a loyalty account. This could add five minutes to a checkout
experience, disincentivizing the customer to engage with the loyalty program.
Now imagine that the same checkout attendant can identify the customer by any
number of data points, not only loyalty number, but also name, first line of
address, email, etc., with faster lookup through auto-complete and fuzzy
matching. A retailer that MongoDB works with does this auto-lookup in store with
Atlas Search in 200-300 milliseconds for optimum customer satisfaction.
Customers and staff also can have difficulty remembering or correctly
identifying products. A DIY amateur or a new employee can’t be expected to know
the exact name or product ID. This is a great use case for search indexing as we
do not know the field in the document or the product attribute that we are
querying against. MongoDB has customers that stock more than 150 million
products. Strong typo tolerance makes life easier for everyone. Back-office
inventory and assortment Flawless purchasing and stock management ensures brick
and mortar and online stores get the right inventory at the right time to
maximize sales and reduce wastage or deadstock. An operator responsible for
distributing products into categories will define in which store shelf a product
needs to be and adjust this depending on customer behavior and contractual
changes with the supplier. Inventory applications will be used on a daily basis
by every operator. These are small internal applications that can have a huge
impact on the overall business, but are often overlooked by large IT programs
for budget or have a smaller IT team. These teams are adopting Atlas Search
because they can get it up and running in as few as three weeks and fully
integrated into their application without taking on more operational overhead.
Customer servicing Long call center or chat conversations wait times have high
operational costs and cause customer churn. It is vital to identify the customer
as quickly as possible by the data they provide: order or customer ID, phone
number, store address, etc. Retailers who have created a “Customer 360” across
their customer relationship management and loyalty systems have created a large
complex pool of data. The ability to run a single query to search across all
available attributes makes it much faster to identify a customer. Search can
also be used to optimize speed and accuracy of results for chat applications and
chat bots who have to answer a large volume and variety of questions. This is a
perfect use case for search with unpredictable user inputs. If answers to the
questions can be searched across the entire knowledge base, speed and relevancy
can be improved. MongoDB has retailer customers building chatbot applications
for internal use cases like an IT team answering common questions, and external
ones. For example, on the ecommerce homepage, a chatbot needs search
functionality to be able to quickly do product lookup, customer identification,
or make a suggestion. Quick and easy search implementation will add to the
customer experience and reduce staff operations. Where your company could add
search functionality It’s time to think beyond the ecommerce search bar. What
are the search workloads within your company’s retail estate? Are there internal
applications that have your frontline or back-office staff frustrated with
inefficient lookups? Is the reason you’re not implementing search today the fact
that it's a heavy lift to add an additional technical component to your
architecture? These are the types of conversations that are driving adoption of
Atlas Search across the retail industry, as businesses persevere in a tough
macro-economic climate to do more with less. Adding vital functionality to
applications without adding complexity is a win for the retailer, the workforce
and the consumer. Want to learn about how MongoDB has integrated Search into the
Atlas Developer Data Platform? Head to the Search solution page to explore more
technical and in-depth resources.
March 29, 2023
Next →
WHAT'S NEW IN ATLAS CHARTS: SCHEDULE DASHBOARD REPORTS TO SHARE DATA WITH YOUR
TEAM
Today, we’re introducing an exciting feature addition for teams using Atlas
Charts . Charts project owners can now schedule dashboard reports to be sent via
email to keep team members informed about key data. This feature has been
heavily requested by some of our largest users as there are many use cases where
dashboards may be valuable to your team, but you don’t necessarily want to
require anyone to do extra work to access and view data. Enter scheduled
dashboard reports in Atlas Charts! In any dashboard that your team relies on for
regular data review, simply schedule a dashboard report. The new Schedule button
can be found at the top right of the dashboard screen: Once you’ve chosen a
dashboard from which to create a report, you will see a variety of options
letting you customize the content and frequency of your report before you
schedule. A report requires basic fields like a name or subject line, recipient
list, and optionally, a message for the body of the email. In addition to a link
to the dashboard in Charts, you can choose whether to attach an image or PDF for
quick reference in the message itself. Finally, you can set a schedule of daily,
weekly, monthly, or quarterly delivery. You can also simply send a single email
if you have a one-time need to share a report. And once you’ve set everything
up, your email will be sent on your defined schedule. As you use scheduled
dashboard reports more and more, we created a Reports page where you can manage
all reports in your project. Note that if you’re on an free tier, you can try
one scheduled report. If you’re on an M2 cluster or higher, you can create up to
100 reports per project. To learn more, please check out our documentation .
We’re always listening to feature requests that will enhance using Charts across
teams, so if you have any requests or feedback, please share them with us here .
Log in to Atlas Charts today to schedule your first report! If you’re new to
Atlas Charts, get started today by logging into or signing up for MongoDB Atlas.
April 13, 2023
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