A round of applause for the 2019 EMEA Elastic Search Awards honorees | Elastic Blog
News

A round of applause for the 2019 EMEA Elastic Search Awards honorees

Without further ado, let’s do this and jump into the 2019 EMEA Elastic Search Awards.

There was a bevy of entrants from Europe, Middle East and Africa (EMEA) vying to become an Elastic Search Award honoree for deploying the Elastic Stack for unique, humanitarian, and business-transformation purposes. After careful consideration, the judges reached their decisions.

The EMEA honorees are: Agroknow, AMPATH, Bayer AG, imec, Department for Work and Pensions UK, and Wamasys.

“There were so many great Elastic Stack use cases from which to choose,” says Robert Trueman, one of the competition’s judges who is the head of software engineering at CDL. “While they were all exceptional, the honorees we chose took their use cases to the next level and really applied them to either do good in the world, to radically transform a business model, and overall they were truly inspiring.”

Valentin Crettaz, data solutions architect at TopHap and an Elastic Search Awards judge, notes that there was a “rich diversity of applications” for the awards program.

“Globally speaking, I was surprised by the level of quality of the majority of the applications we had to evaluate. Over the last decade, I’ve seen the Elastic Stack being used in so many different use cases that I often think I had seen them all. However, I must admit that I’ve been literally stunned by the way some of the applicants are using Elastic,” Crettaz says.

The EMEA awards come on the heels of 2019 Elastic Search Awards ceremonies for the Americas region, the APJ region, and for the public sector

The EMEA honorees were announced Oct. 29, 2019 at the Elastic{ON} Amsterdam tour event. All honorees receive an Elastic Online Training Subscription, access to a discounted Elastic Cloud offering, and other prizes to honor their outstanding use cases.

You Know, for Search! Awards (Business Transformation)

Our judging panel reviewed the applicants based on their projects' importance, potential for growth, and whether the projects have fostered the breakdown of data silos.

Bayer AG

Bayer is a German life science company with more than 150 years of experience in healthcare and agriculture. With its innovative products, Bayer is contributing to finding solutions to some of the major challenges of our time. FAIRification of data, Bayer says, is a prerequisite to be able to answer important questions near and dear to a pharmaceutical company in a convenient and efficient way: “I want all data ever published on gene X or disease Y.”

In their project honored by the judges, Bayer developed a Kappa architecture with the Elastic Stack and Confluent Kafka in a bid to provide FAIR access to the wealth of licensed data from outside sources relevant to pharma business processes across the pharma value chain at Bayer. 

Bayer is integrating a large and diverse set of raw, textual data sources — 8 terabytes and several billion pages of raw text — by applying different normalization, mapping, and semantic enrichment algorithms to harmonize the data. Once all data has been processed as desired, it is ingested with Logstash into Elasticsearch (as a managed cloud solution), which hosts all integrated data and acts as the single source of truth and provides access in a scalable and convenient way both for programmatic use and for access by end users. 

On top of Elasticsearch, Bayer builds data, information, and knowledge services, visualizations with Kibana, in addition to alerting systems with Watcher, Elastic APIs, and custom UIs. 

“We are delighted and happy about the recognition we receive. It is also a confirmation that we have been choosing the right scalable architecture and design patterns to support our use case,” says Astrid Rheinländer, computational scientist at Bayer. “We see a huge potential for this application in the future with regard to the automation of existing processes and by providing APIs to the organization as we plan to integrate more and more semantically enriched data sources into the system.”

Department for Work and Pensions

The Child Maintenance Service is an agency within the Department for Work and Pensions in the UK. It handles financial support for separated households and determines how parents split costs for their shared responsibility in bringing up a child.

The Child Maintenance Service (CMS) currently uses Siebel to handle caseloads and manage citizen requests. A new Digital Experience Monitoring (DXM) project was set up, harnessing the Elastic Stack, to help provide greater insight into the performance of the Siebel system. This monitoring would help the Live Service Support team be more proactive in ensuring system performance for caseworkers and citizens. In addition, the project would provide a targeted view of core system performance, and improve capabilities to analyze system data both historically and in near real time.

The data processed by DXM comes from a wide array of sources: Siebel Application response measurement, telephony logs, Oracle BPM system and application logs, IBM WebSeal logs, various other custom application logs, and database queries.

Data is extracted every 10 minutes from the Siebel application and shipped to Logstash to capture critical performance data and enrich reporting on specific areas of the business. Data for all other applications comes in near real time, giving the Live Services Support team access to performance data instantly.

Logstash ships, parses, and loads data from a variety of sources. Elasticsearch stores, searches, and analyses the data. Every event created is stored on Elasticsearch as an individual document under a defined index. Kibana dashboards make deep dive analysis possible — such as multi-level aggregation, percentile analysis, baseline comparison, active users, site statistics, etc.

“We as a team are delighted and somewhat overwhelmed to be receiving such a prestigious award. We will all be smiling for a long time. We have been on a very challenging journey and through exceptional teamwork we have been able to totally transform our business, specifically our system monitoring capability,” says the developers on the project, Suzy Robertson, Anne McLeod and Simon Ramsey.

Cause Awards

Our EMEA judging panel reviewed the applicants based on a project's measurable impact, reach, and inspiration for bettering the world.

Wamasys

Wamasys offers software to manage the distribution of water and other essential services, from meter reading to invoicing, and from payment to reporting. Today, Wamasys, of France, is used in the Philippines, Ivory Coast, and Bangladesh to deliver drinkable water

to 35,000 inhabitants of disadvantaged areas. Each month this represents 6,000 contracts and about 350,000 invoices issued and paid, in addition to 180,000 water consumption records.

This data is stored in Elasticsearch in various indices (water, contract statistics, invoicing) and visualized with Kibana in dedicated dashboards. With the dashboards, water company managers have access to data such as consumption per inhabitant, median monthly water consumption, average consumption per area, and evolution of the rate of late payment. They can filter this data instantaneously based on consumer profile, location, and other factors.

All of this helps Wamasys’ goal to improve access to water and reduce water prices in underprivileged areas. The United Nations estimates that 2.1 billion people lack access to adequate drinking water, and 340,000 children die annually because of unsafe drinking water and poor sanitation. In slums, people pay substantially higher prices for safe water because water companies are reluctant to deliver there because of high rates of late payment, higher maintenance costs, and other operational risks.

Waymays’ software and services is designed to entice water companies to operate water service in these localities by providing them with an affordable solution, and decreasing operational risk. Wamasys seeks to decrease late payments through very frequent invoicing and flexible payment (door-to-door, in agency or with a mobile), and to identify operational issues more quickly thanks to reporting and analysis with the Elastic Stack.

With smart meters, geolocation, and machine learning, Wamasys enhances water companies operational efficiency, provides real-time alerts in case of anomalies, and gives insights on water consumption habits and predicts future consumption and invoicing patterns. 

“ElasticSearch and Kibana are key pillars of our invoicing solution. Our clients are providers of water and other essential services in underprivileged areas, and  they carry out very frequent invoicing in order to secure appropriate payment collection rates. ElasticSearch allows us to deliver strong performance even with such high volumes,  300,000 invoices monthly, and Kibana is the key tool to visualize KPIs at a higher level and identify rapidly operational issues such as water leaks or a customer in difficulty,” says Laure d’Azémar, co-founder of Wamasys.

AMPATH

The Academic Model Providing Access to Healthcare (AMPATH) was founded in 2001 in Kenya to combat one of the world’s worst epidemics: HIV. AMPATH is a partnership between the Kenyan Ministry of Health, Moi University in Eldoret, Kenya, and a consortium of American universities. Today the Elastic Stack is used by AMPATH to create visualizations from around the country’s clinics--allowing them to create actionable plans for better care. 

In the late 1990s the HIV epidemic ravaged Kenya, and AMPATH, in partnership with various donors, created a free healthcare system in western Kenya to care for patients living with HIV. Over time, AMPATH has helped care for more than 150,000 patients and logged over 7 million patient encounters. More recently, AMPATH has begun a universal health care program. Leveraging the investments made via HIV care, AMPATH is now creating a care system in partnership with the Kenyan Ministry of Health premised on a primary care network combined with a universal health insurance system that will provide comprehensive care for all patients, regardless of ability to pay.

A key component of AMPATH’s ability to provide care across geographically dispersed and low resource areas is the AMPATH Medical Record System (AMRS). This is a customized version of OpenMRS, an open source medical records system. In 2015, AMPATH made the leap to using the electronic health record directly at the point-of-care for all patient visits at high volume facilities. The point-of-care electronic medical record system supports various clinical workflows within the care system, has modules for patient review, data collection (customized interactive forms with validation and skip logic), decision support (when to order various tests), and clinic management (scheduling, missed appointment tracking, and Ministry of Health reports). 

Since 2015, more than 700 clinical providers at 30 sites have recorded over one million patient encounters. Initially, AMPATH created custom dashboards to make data available to key decision makers such as clinicians, Ministry of Health officials, and AMPATH management. 

However, the infinite demand for new data visualizations was impossible to meet via custom code. In 2017, AMPATH began experimenting with the Elastic Stack to fulfill this critical organizational need. AMPATH started development on an extract, transform, load (ETL) process to move data from the electronic medical record MySQL database through Logstash and into Elasticsearch. Kibana is then used to generate dashboards for HIV patient monitoring. 

"We are so honored to be recognized by Elastic for our work utilizing the ELK stack for HIV and chronic disease management in Kenya. We believe our dashboards create a foundation to convert complicated health care data into actionable information, leading directly to improvements in the quality of care we are able to deliver,” says Jonathan Dick, AMPATH’s chief medical officer.

Cluster Awards (Technology Innovation)

Our judging panel reviewed the applicants based on inspiration, uniqueness, and whether the project required a leap of faith that the Elastic Stack would be the engine that powered the successful solution.

imec

The imec Innovation Services and Solutions division is the semiconductor manufacturing division of a leading nano-electronics research institute, imec, of Belgium. It helps innovators, entrepreneurs, and universities realize their ideas in hardware and software by providing design, low-cost prototyping, and volume production. 

Our judges honored imec for their project of treating their manufacturing supply chain as a social network of sorts. imec uses Elastic’s Graph plugin to form a business partner network and applies various graph centrality theorems to analyze the network. With this, imec is able to get more insight in their business model, and see key factors which influence its functionality and future trends.

The Graph plug-in links existing data and documents without any preprocessing steps. Through the Graph API, imec programmatically built graph models of its manufacturing supply chains as a social network from 2004 as it evolved to today. The Elastic Stack enables imec to pack together storing, searching, and advanced analytical capabilities on top of large amount of heterogeneous, linked data. 

“As the manufacturing division of imec, we are responsible for developing new businesses and business lines based on advanced integrated circuit technology. The ability of Elasticsearch to help us visualise the complex network of suppliers, customers, and projects in terms of a social graph has proven invaluable,” says Petr Dobrovolny, senior researcher at imec. “It has enabled us to understand our business on a more fundamental level and to help us plan for the future with more targeted business models.”

Agroknow

Agroknow has developed FOODAKAI, which aims to collect all food safety data announced worldwide. It is searchable and users are able to perform intelligent analytics on top of the data.

The Greek company acquires the data from scraping relevant websites that may involve food recalls, agricultural commodity import/export data, price data on raw materials, and respective legislation. The team behind FOODAKAI consists of software and data engineers, food safety, and domain experts. Its customers include people working in the QA and R&D departments of food companies who need to be alerted as quickly as possible for announced food recalls. FOODAKAI also helps its customers perform risk analysis for finished or new products as well, and allows researchers in the field of food safety to access relevant data to enhance their work. 

Most of the data collected by FOODAKAI is text-oriented, multilingual, and may come in various formats. All of the collected data is stored into Elasticsearch. In terms of volume and variety, about 30 entity types are tracked, including food recalls, pricing data, food companies, and lab tests — leading to a total of about 65 million documents. 

An important step of FOODAKAI’s ETL process is the identification of the reason (i.e., bacteria) of a recall, the product brand involved, the main ingredient of this brand, the manufacturer, and countries affected. By storing vocabularies of raw materials, hazards, countries, and food companies in Elasticsearch, text classification and annotation of the raw food recalls collected is automatically performed and ultimately is readily searchable.

“We are really delighted to receive the EMEA Elastic Search Award! We have been heavily using the Elastic Stack in FOODAKAI for applications varying from storing data collected by our crawlers to text mining and classification,” says Mihalis Papakonstantinou, Data Services Leader at Agroknow. “Integrating the Elastic Stack into our backend platform has also proven valuable in allowing NER-powered freetext searches over the collected data and of course has made very easy to monitor and visualize the usage of the whole platform.”

Congratulations honorees. Keep up the good work!