Informationssicherheit auf Cloud Plattformen
CAF bietet seinen Kunden eine digitale Plattform, auf der sie einige zustandsbasierte Wartungsaufgaben ausführen können, um ihren aktuellen Betriebs- und Wartungsprozess zu verbessern. Für die Weitergabe dieser Informationen muss jedoch ein hohes Maß an Datenschutz und Sicherheit gewährleistet werden.
Success Case: CAF
Information Security on Cloud Platforms
Multinational group that supplies comprehensive transit solutions and has a annual turnover of 2BN Euros.
THE CHALLENGE
CAF provide its customers with a digital platform where they can perform some condition-based maintenance tasks improving their current operation and maintenance process. However, sharing this information requires granting high levels of privacy and security.
THE SOLUTION
Keepler delivered a three weeks audit and consultancy project led by two AWS Professional Architect Certified engineers with Big Data and Security specialties certifications with more than five years of experience working in D&A on AWS.
THE RESULT
This project was the input for the subsequent development of the proposed controls and mechanisms. LeadMind’s product team with the support of an infrastructure and security expert Keepler engineer have implemented most controls and will face the ISO/IEC 27001 audit process during Q12021.
Landezone und Datenumgebung für Analytik und Geschäftsanwendungen.
Der Kunde möchte in einem neuen Markt tätig werden, wobei er die Zeit bis zur Markteinführung verkürzt und die Möglichkeit hat, schnell zu skalieren, sobald neue wichtige Anwendungen zur Gewinnung von Marktanteilen hinzugefügt werden.
Success case: IMAGINA ENERGÍA
Landing Zone and Data Environment for Analytics and Business Applications
Leading Spanish energy company in the commercialization of renewable energy.
THE CHALLENGE
The client is willing to run its operations in a new market, so they need to reduce time-to-market with the ability to scale rapidly as new crucial applications are deployed to capture market share. Privacy and security are the top priorities of the company in this highly regulated sector, so there is a need to apply strong principles of security, governance and best practices.
THE SOLUTION
Keepler deployed a landing zone solution using AWS Control Tower in a fast and scalable way, activating the necessary security mechanisms. In addition, a data lake was provisioned using AWS Lake Formation to centralize the data of the systems in a standard and secure way. Once the deployment is complete, Keepler is operating the client’s infrastructure.
THE RESULT
The deployment of the solution proposed by Keepler has been carried out in matter of days, reducing the TCO of the solution by 50% compared to implementations not based on native services such as Control Tower or Lake Formation.
Herstellung von Ölderivaten Data Lake
Steuerungssysteme für die Raffinerieherstellung sind sehr teuer und in der Datenspeicherung und -verarbeitung sehr begrenzt.
Success Case: CEPSA
Data lake manufacturing
Multinational group in the energy sector that integrates the oil, gas and electricity and has a annual turnover of 20BN Euros.
THE CHALLENGE
Refinery manufacturing control systems are very expensive and very limited in data storage and processing.
THE SOLUTION
Keepler designed and deployed a Manufacturing IoT Analytics platform in the public cloud that is able to process and store hundred of millions of IoT events per day.
THE RESULT
Refinery operators can access to business enriched event historic data to enhance refinery operations. Data Scientist can build ML models from DataLabs. IoT data access is available for new use cases.
Multi-client Big Data Plattform für Optimierung der Zugwartung
Der Kunde möchte den ROI der Wartungsdienste durch die Nutzung der von den Zügen generierten Daten erhöhen. Die Sensordaten der Züge sind massiv (2 GB pro Einheit und Tag) und komplex zu analysieren.
Success Case: CAF
Multi-Client Big Data Platform for Train Maintenance Optimization
Multinational group that supplies comprehensive transit solutions and has a annual turnover of 2BN Euros.
THE CHALLENGE
The client is willing to increase the maintenance services ROI by leveraging the data generated by the trains. Trains sensor data is massive (2Gb per unit per day) and complex to analyze.
THE SOLUTION
Keepler designed and deployed a Big Data platform in the public cloud that is able to ingest and store sensor data arriving from the trains. The data is used for breakdown forensics and predictive maintenance.
THE RESULT
The client has launched a digital train suite of services based on data that make its maintenance services more competitive in costs and service level.
Modellierung der Ausbreitung von Covid-19-Infektionen
Obwohl täglich neue Daten zu COVID-19 verfügbar sind, sind die Informationen über die biologischen und epidemiologischen Eigenschaften von COVID-19 nach wie vor begrenzt und es besteht Unsicherheit für fast alle Parameterwerte.
Success Case: CAM
Modeling the Spread of Covid-19 Infection
The Regional Government of Madrid Region.
THE CHALLENGE
Although new data on COVID-19 is available daily, in a pandemic situation it is relevant to know the evolution of the spread to make preventive decisions.
THE SOLUTION
Keepler developed and implemented an interactive dashboard to visualize and understand in a better way the key drivers of the pandemic and its implications. Based on machine learning technologies, it allows developing models at a regional level to evaluate and forecast the course of the pandemic.
THE RESULT
Forecasts are strongly influenced by the reliability of the data. Having an early warning system capable of obtaining a holistic view of the evolution of the pandemic and the incidence of the virus among Spanish regions, allows to detect changes in the distribution of these data and make decisions based on them.
Erkennung von Anomalien in Kryogenen Pumpen
Durch die Beobachtung von abnormalem Verhalten in den Daten kann die Wartung geplant werden, bevor es zu einem Ausfall kommt, der zu Produktionsverlusten und Verschlechterung des Gases führen würde.
Success Case: ENAGÁS
Anomaly Detection in Cryogenic Pumps
International leading company in natural gas infrastructure with a presence in 8 countries.
THE CHALLENGE
Maintenance of pump equipment is one of the most important tasks associated with the operation of process plants and it was implemented either on a routine basis or after the failure of equipment. Enagás wanted to change this procedure and anticipate possible failures by observing abnormal behaviours in the data.
THE SOLUTION
Through the proposed machine learning model, the process evolves to a data-driven predictive maintenance system. In addition, an API has been developed so that the trainings, inferences or updates of the models can be performed easily by business users.
THE RESULT
This solution provides Enagás a model for every pump helping their technical team to evaluate the functioning of every pump individually,, reducing costs and intervening only when strictly necessary. Thanks to the API, users can perform multiple trainings/inferences faster, making this task more agile.
Schutzausrüstungserkennung mit KI und Edge Computing
Raffinerien sind Arbeitsplätze, an denen die Mitarbeiter eine Sicherheitsausrüstung tragen müssen. Es ist schwer zu erfassen, wann Mitarbeiter diese Ausrüstung nicht tragen.
Success Case: CEPSA
Personal Protective Equipment Detection Using Video Analytics
Multinational group in the energy sector that integrates the gas and electricity and has a annual turnover of 20BN Euros.
THE CHALLENGE
Workplaces as refineries are places where workers must wear specific security material. It is hard to detect when workers are not wearing this material.
THE SOLUTION
Design and deployment of a model to detect the use of protective equipment (helmet) and deployment in a edge computing device (camera with GPU processing device).
THE RESULT
This initiative is part of a pilot.
Plattform für den Verkauf von Datenlösungen
Der Klient verfügt über eine On-Premise-Plattform, die auf relationaler Datenbanktechnologie basiert, nicht skalierbar ist oder die Flexibilität hat, verschiedene Datentypen zu verwalten.
Success case
Platform for Selling Data Solutions
Data trading company specialized in marketing data.
THE CHALLENGE
The client has an on-premise platform based on relational database technology, being unable to scale, or to have the flexibility to manage different data types. In addition, the current solution is neither agile nor flexible enough to develop tailor-made data solutions for his clients. The client wants to move to a Data Lake-based solution he can manage autonomously after the deployment.
THE SOLUTION
Keepler deployed a Data Lake solution with ingestion and synchronization from the client’s current Oracle database systems using Amazon DMS. The platform also allows the loading of time series data. In addition to a central Data Lake with all the raw information, Keepler provided a mechanism using Amazon EMR and Glue Data Catalog to implement different use cases, being these use cases manifestations of the analysis of the central Data Lake data customized for each client.
THE RESULT
This solution allowed the client to move from an information-on-request delivery model to a completely self-service model that is much more scalable and that facilitates cross-selling of services.
Zentralisierte Cloud-Plattform für Datenmanagement und BI
Je höher die Anzahl von Excel-Dateien ist, desto aufwändiger wird das Verwalten und die Verfolgung dieser Daten. Bei einer hohen Anzahl von Excel-Dateien vervielfachen sich außerdem Fehler und Probleme beim Auffinden von Daten.
Success Case
Data Management and BI Centralized Cloud Platform
Leader investor in leisure Hotels
THE CHALLENGE
As the amount of Excel files grow, the effort to manage them and to keep track of them is very relevant, and the mistakes and problems finding data multiplies. The client also uses a specialized SaaS solution to aggregate operational hotel information, but the solution does not integrate external information and proprietary market information. The client cannot also deploy ML models to increase the data’s value and provide more significant support to hotel managers.
THE SOLUTION
Keepler developed and deployed a Data Management solution based on analytics services, processing and reporting Cloud tools. Besides, Keepler focused on helping heavy-users of Excel transition to a data consumption model based on centralized repositories and governing the use of data.
THE RESULT
The client can now capture information form many different internal and external sources, processes it, and show the treated information to cover different business use cases. Keepler is working with the client to develop new use cases based on Machine Learning, such as dynamic price optimization and automatic evaluation of real estate potential.
Kunden 360 Vision Plattform
Der Kunde verfügt über eine Big-Data-360-Plattform, in der Anwendungsfälle (Berichts- und Data Science-Modelle) bereitgestellt werden, auf die verschiedene Geschäfts- und Projektbereiche zugreifen. Nach Abschluss der Bereitstellung ist der Kunde in der Lage, Kosten für Support-Services und die Entwicklung der Plattform zu sparen.
Success Case
Customer 360 Vision Platform
Leading spanish media and entertainment company.
THE CHALLENGE
The client has a Big Data 360 platform where different use cases have been deployed (reporting and data science models) which are accessed by various business and project areas. Once the deployment is complete, the customer is willing to save costs on support services and platform evolution.
THE SOLUTION
Audit of „best practices“ of the architecture, optimization and automation of the platform using „Infrastructure as code“. Creation of information dashboards for the different business units of the company, with the aim of optimizing the sale and purchase of advertising.
THE RESULT
Cost savings both in infrastructure and personnel by centralizing all the information in a single repository and evolution of the platform to support different use cases that allow optimizing their business. Errors and inefficiencies in the data ingestion, treatment and quality processes were reduced by 75%.
Automatisierung der Dokumentendigitalisierung
2019 definierte dieses Sicherheitsunternehmen einen ehrgeizigen Plan für die digitale Transformation mit dem Ziel, die überwiegende Mehrheit der Prozesse des Unternehmens zu digitalisieren und zu automatisieren.
Success Case
Automation of Document Digitization
Security company leader in the Spanish market.
THE CHALLENGE
In 2019, this security company defined an ambitious master plan for digital transformation, with the aim of digitizing and automating the vast majority of the company’s processes. In this context, the need arises to automate the digitization of invoices, integrating it, through RPA, with the scanning and matching flow with the ERP.
THE SOLUTION
Keepler has designed and developed an automated and intelligent invoice entity extractor based on its unstructured data (UDI) framework, capable of extracting these invoice entities in several languages and performing automated actions (sending data to RPA for integration with ERP).
THE RESULT
+90% accuracy in extracting entities from invoices in different languages.
Integration of the invoice digitization flow with the ERP.
Portugiesische Autobahngebührenzahlung mit einem Chatbot
Portugiesische Autobahnen haben Mautgebiete. Mit speziellen Geräten werden dem Kunden die Kosten der Maut in Rechnung gestellt. Manchmal wird das Gerät nicht erkannt und der Kunde wird später aufgefordert, über ein Zahlungsgateway zu zahlen.
Success Case
Portuguerse Highway Toll Payment Using a Chatbot
Leading multinational services company
THE CHALLENGE
The Portuguese highways have toll areas where special devices are used to charge the cost of the toll to the customer. Sometimes the device is not detected and the customer is later requested to pay through a payment gateway. Queries are frequent and the current payment gateway is difficult to use.
THE SOLUTION
Keepler has designed a ChatBot platform that provides a comprehensive Q&A functionality along with an easy to use payment gateway.
THE RESULT
Unpaid toll rate is reduced.
Automatisiertes Störfallmanagement im Stromverteilungsnetz
Mit über 2 Millionen installierten intelligenten Zählern möchte der Klient einen besseren Service für seine Kunden bieten, indem er Vorfälle im Netz vorhersagt.
Success Case
Automated Incident Management in the Electrical Distribution Network
Multinational group in the energy sector that integrates the gas and electricity and has a annual turnover of 20BN Euros.
THE CHALLENGE
With over 2 million smart meters deployed, the customer is willing to provide a better service to its clients by forecasting incidences in the grid.
THE SOLUTION
The use of remote management information allows the early identification of incidents on the electricity grid using machine learning, as well as the launch of proactive maintenance actions.
THE RESULT
Reduction of 60% in the time to detect and solve incidences.
Optimierung des Produktionsprozesses
Untersuchen der Leistung von Arbeitsabläufen, um die Parameter zu optimieren, die die Erzeugung des Endprodukts beeinflussen. Und das alles, ohne die Produktion, die sich auf höchstem Niveau befindet, zu benachteiligen.
Success Case
Production Process Optimization
Multinational group in the energy sector that integrates the gas and electricity and has a annual turnover of 20BN Euros.
THE CHALLENGE
The Shanghai chemical plant aims to study, with a data-driven approach, the performance of its workflows to optimize the parameters that influence the manufacturing of the final product. All this without penalizing the production that is at its highest level.
THE SOLUTION
Keepler has carried out a descriptive analysis of the variables of temperature, pressure, etc. to identify optimal performance conditions, and has developed an optimization model that indicates which parameters to adjust to replicate the optimal threshold, ensuring thereby a more efficient process.
THE RESULT
Reduction of up to 5% in the volume of required components to obtain the product.
Erforschung der Qualitätsdata
Identifizierung und Untersuchung der Variablen, die sich auf die Qualität hergestellter Flaschen auswirken, so dass diese Variablen verwaltet werden können, um den Anteil der zurückgewiesenen Flaschen zu reduzieren.
Success Case
Plastic Bottles Manufacturing Quality Data Exploration
Multinational company dedicated to providing innovative rigid plastic packaging solutions through 44 plant-in-a-plant facilities and nine “nearby” facilities worldwide.
THE CHALLENGE
Identification and study of the variables that impact in the quality of the bottles manufactured so those variables can be managed to reduce the ratio of bottles rejected.
THE SOLUTION
Keepler deployed a data exploration environment in AWS and set up an ensemble of two Data Models using 30 out of the hundreds of existing variables generated from SIDEL machines that influenced the most in the quality of the bottles manufactured.
THE RESULT
Keepler provided a decision tree with the ranges of values of neck temperature, blowing pressure and others. By applying combinations of those settings, the reduction of rejected bottles was between 5% and 20%.
Bankbetrieb Data Lake und Dashboarding
Eine digitale Bank wollte eine komplette Übersicht über die Hauptprozesse, einschließlich der digitalen Anmeldung und des Lebenszyklus der wichtigsten Produkte, wie Hypotheken, Kredite, Kreditkarten, etc. Die Informationen sind verstreut und die operativen KPIs sind nicht definiert.
Success Case
Bank Operations Data Lake and Dashboarding
Spanish Digital Bank.
THE CHALLENGE
The digital bank wanted to have an holistic view of the main processes including digital enrollment and the life-cycle of the main products, as mortgages, loans, credit cards, etc. The information is disperse and operational KPIs are not defined.
THE SOLUTION
Keepler defined with the bank +300 operational KPIs and designed the data flows from both internal and external sources in order to calculate and display the KPIs. Keepler also designed a comprehensive set of dashboards with self-analytics capabilities.
THE RESULT
The bank used this information to enhance operational processes, also fixed the calculation of indicators that was previously misinformed or wrongly calculated.
Datenexplorationsumgebung Migration in die Cloud
Die Explorationsumgebung in einer On-Premise-Cloudera-Installation muss aufgerüstet werden, um mehr Daten und mehr Benutzer unterzubringen.
Success Case
Data Exploration Environment Migration to the Cloud
French multinational telecommunications corporation. It has 266 million customers worldwide.
THE CHALLENGE
The exploration environment in an on-premise Cloudera installation has to be upgraded to accommodate more data and more users.
THE SOLUTION
Migration of a 250Tb Data Lake to the cloud, including data ingestion, processing using Spark and data consumption using a tailored data scientist environment. The new data exploration platform is built using native public cloud services and fully automated. It provides services to +200 data scientists.
THE RESULT
Undisclosed savings in Cloudera licenses.
Automatisierte Datenanalyse-Umgebungen und ML-Pipeline für ein grosses Data-Science-Team
Mit einem Team von über 200 Datenwissenschaftlern und einer On-Premise-Plattform in Cloudera war der Kunde gezwungen, eine neue Datenumgebung zu schaffen und die Kosten in Grenzen zu halten.
Success Case
Automated Data Analysis Environments and ML Pipeline for a Large Data Science Team
French multinational telecommunications corporation. It has 266 million customers worldwide.
THE CHALLENGE
With a team of 200 data scientist and an on-prem Cloudera platform, the customer was struggling to create new data environments and keep costs in line.
THE SOLUTION
Keepler designed a Big Data platform to mirror the Cloudera capabilities with native services as S3 and EMR and migrated 250Tb of compressed data to cloud. Also automated the ML pipeline with DataLab environments that can be launched on-demand.
THE RESULT
Reduced the time of delivery of Data Scientist environments from days to minutes. Improved the performance of current Spark processes.
Intelligente Postsortierung
Ein Versicherungsunternehmen erhält mehr als 100k Mails pro Monat zu verschiedenen Vorgängen und Anträgen. Ein Expertenteam muss alle E-Mails lesen und an das entsprechende Managementteam weiterleiten. Dieser Prozess ist kostspielig und anfällig für menschliche Fehler.
Success Case
Email Classification Engine
Large Spanish Insurance Group.
THE CHALLENGE
The insurance company receives more than 100k emails per month related to different processes and requests. A team of experts must read all emails and forward them to the appropriate team. This process is costly and prone to human mistakes.
THE SOLUTION
Keepler designed and developed an automatic email classifier that is able to OCR attachments (Textract), extract topics, intents and forward the mail automatically to the appropriate team (Sagemaker).
THE RESULT
+90% precision in the classification.
Reduction of 20% of the mail analyzed due to the detection of spam.
Modellierung des Online-Lebenszyklus von Kunden und Empfehlungsmaschine
Mit mehreren Marken und E-Commerce-Plattformen wollte unser Kunde eine ganzheitliche und einheitliche Übersicht über die Kunden und Verkäufe aller Marken erhalten. Mit Hilfe dieser Informationen sah der Kunde vor die Online-Verkäufe zu steigern, indem er jedem Kunden eine personalisierte Empfehlung zukommen lässt.
Success Case
Customer Online Life-Cycle Modeling and Recommendation Engine
Leading Spanish Fashion Retailer.
THE CHALLENGE
With several brands and e-commerce platforms, our client wanted to obtain an holistic and unified view of customers and sales in all brands. Using this information, the client wanted to increase online sales by targeting every customer with a personalized recommendation.
THE SOLUTION
Keepler deployed a Big Data platform uploading customer interaction data (Google Analytics) and sales identifying customer using cookies, loyalty card, etc, and associating the customer with sales from the ERP backoffice platform. Even brick&mortar sales data were used to further personalize the recommendations.
THE RESULT
Internal users have a unique view of the ecommerce platforms in all brands and sales were boosted thanks to the combination of recommendation in the portal and a tailored newsletter automatically sent to known customers.
Logistik-Prognose
Der Achsschenkel ist ein wichtiges und teures Bauteil des Autos. Wenn dieses Teil nicht vorrätig ist, muss die ganze Fabrik stillstehen. Ein Autohersteller wollte prognostizieren, wann die Achsschenkel in den Fabriken eintreffen werden.
Success Case
Steering Knuckle Logistics Forecasting
Large Spanish Car Manufacturer.
THE CHALLENGE
The steering knuckle is a key and expensive component of the car. If there isn’t stock of this piece the whole factory has to stop. The car manufacturer wanted to forecast when the knuckles will arrive at the factories in two Spanish cities.
THE SOLUTION
Keepler integrated an IoT solution based on Cellnex and devices attached to the racks of knuckles. Each device can track the position of the rack and if it is moving.
THE RESULT
As the application is rolling out, trucks are being monitored and stock can be better adjusted. By providing a steady flow of steering knuckles the client can keep an average of 2.000 cars produced per day per factory.
Dynamische Gaspreisgestaltung in einem Netzwerk von Tankstellen
Erhöhung des Durchschnittspreises von Ölprodukten (Benzin, Diesel, etc.) und der Verkaufsmenge dieser Produkte an 1.200 Tankstellen, ohne die Nachfrage zu beeinflussen.
Success Case
Dynamic Gas Pricing in a Network of Gas Stations
Multinational group in the energy sector that integrates the gas and electricity and has a annual turnover of 20BN Euros.
THE CHALLENGE
Increase average price of oil products (gasoline, diesel, etc) without affecting the demand.
THE SOLUTION
Design training and deployment of +1.200 data models to dynamically adjust gasoline price in each gas station according to demand elasticity, weather, city events, and a business rule engine.
THE RESULT
Increase of 2 cents of Euro of the average gas price.
Reduzierung der Look-to-book-Ratio durch Kundensegmentierung und White-Lists
Bedbank ist ein Großhändler für Hotelzimmer. Reisebüros suchen über die Anwendung Bedbank nach verfügbaren Zimmern und Hotels. Der Kunde wollte das Suchvolumen reduzieren, indem er jedem Kunden eine individuelle Auswahl an Hotels empfiehlt.
Success Case
Look-to-book Ratio Reduction Through Customer Segmentation and White-lists
Leading Spanish Bendbank.
THE CHALLENGE
A Bedbank is a wholesaler of hotel rooms. Travel agencies browse room and hotel availability through the Bedbank application. The customer wanted to reduce the volume of searches by recommending a personalized set of hotels to each customer.
THE SOLUTION
Keepler deployed a data product that create white-lists of hotels and locations for every travel agency according to a segmentation based on a customer profile and historic bookings and searches. The segmentation and the white-lists are periodically and automatically calculated in order to further reduce the look-to-book ratio.
THE RESULT
Look-to-book ratio were reduced in a 10% thus reducing the operation costs of the bedbank accordingly.
Datenexploration in einem Telemetrie-Netzwerk
Der Kunde ist bereit, Wasserverbrauchsmuster (insbesondere betrügerische) zu identifizieren und auch die Erkennung und Korrektur von Messlücken zu automatisieren.
Success Case
Data Exploration in a Smart-meter Network
Water Management Company.
THE CHALLENGE
The customer is willing to identify water use patterns (specifically fraudulent) and also automate the detection and fixing of gaps in measures.
THE SOLUTION
Keepler designed a Big Data platform in the cloud that can process and store smart-meter data. A set of data models were also deployed to manage gaps and identify anomalies.
THE RESULT
The data quality of the entire process was improved, increasing the accuracy of the customer’s invoice estimation. During the project, the identification of potential fraudulent cases, leaks or flow-reversal cases helped the customer’s operations area to detect issues in advance.
IoT-Ökosystem für Mehrwertdienste
Der Kunde möchte die Service-Treue erhöhen, indem er Mehrwertlösungen auf Basis von IoT-Geräten anbietet, die mit dem Mobilfunk- und Internet-Router verbunden sind.
Success Case
IoT Ecosystem for Added Value Services
Telecommunications Operator.
THE CHALENGE
The client is willing to increase service stickiness by providing value added solutions based on IoT devices connected to the mobile and internet router.
THE SOLUTION
Keepler designed and deployed a IoT real time analytics end event-driven platform that enables the intelligent correlation of events to launch actions (alarms, other IoT events, etc) and obtain insights from the customers.
THE RESULT
The client has provided its customers with an advanced app that allows them to monitor the state of their home and its habitants, with services ranging from intrusion detection to assistance to the elderly.
Pseudonomysierung sensibler Daten
Erfüllung der EU GDPR-Anforderungen in Bezug auf den Datenschutz, Anwendung von Pseudonymisierungstechniken auf PII-Daten, die in einem AWS S3 Data Lake von ~300TB gespeichert sind.
Success Case
Sensitive Data Pseudonymization
French multinational telecommunications corporation with 266 million customers worldwide.
THE CHALLENGE
Meet the EU GDPR requirements in terms of data privacy, applying pseudonymization techniques to PII data stored in a ~300TB AWS S3 Data Lake.
THE SOLUTION
Built an advanced, cloud-native, and event-driven architecture based on AWS EMR, AWS Lambda, AWS SNS, and AWS S3 to de-identify historical data and on-the-fly data making use of direct integrations with operational services (orchestration flow and data catalog). The platform also allows users to request de-identify or identify operations on-demand and it also provides a complete layer of monitoring and alerts.
THE RESULT
Data users will not be allowed to see or misuse PII information that could potentially lead to an unexpected data breach, while they can keep working as usual with the encrypted data.
Wenn Sie mehr wissen möchten oder wünschen, dass wir einen Vorschlag für Ihre spezifische Anwendung entwickeln, kontaktieren Sie uns und wir werden uns mit Ihnen darüber unterhalten.
