Global databases on the example of Betfair company

Watch full webinar here: https://bit.ly/3nxGFam Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails. In this session you will learn about: - The role of a virtual semantic layer in self service initiatives - What are the key capabilities of Denodo’s new Data Catalog - Best practices and advanced tips for a successful deployment - How customers are using the Denodo’s Data Catalog to enable self-service initiatives

Denodo’s Data Catalog: Bridging the Gap between Data and Business (APAC)

One of the most fruit aspects of being chosen as a partner bank is that you can have a backend that can communicate directly with the client's system. With this partnership, Banco Santander has led to running a large series of third party applications on their banking system for many years. Banking is the most regulated sector to make day-to-day operations more interesting. Adapting the system to regulation is not optional and is mandatory. For today's banks internal and external audits are an important routine. Furthermore, considering that SCIB is a global player, this pattern is repeated in each country where the group exists. It can be said that it is a really interesting compound! Various kinds of third party systems are installed in many countries, coexisting with our centralized system, transmitting information mutually, being adjusted manually, data is aggregated / integrated at the back office. Spaghetti comes to mind when considering that all data comes and goes without delay. More and more, regulators and auditors are able to perfectly identify the origin of each data. This often means that you need to manually interfere in order to fully locate the data. Javier Nieto, active in Banco Santander's corporate investment banking architecture and innovation department, talks about integration challenges that Santander experienced when building an on-demand Data Lake to move to global big data.

Journey to Big Data: Main Issues, Solutions, Benefits

DataWorks Summit

Flash session -streaming--ses1243-lon

DataWorks Summit/Hadoop Summit

Organising the Data Lake - Information Management in a Big Data World

In this presentation, Dave Kay, Data Consultant within the Analytics and Architecture group at Zurich Insurance, explains how Zurich is modernizing their data infrastructure using data virtualization to accelerate delivery of mortgage insurance and intra-day operational reports to business analysts, salespeople, underwriters, managers, and actuarial staff. This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/GLPPg2.

Modernizing Data Architecture using Data Virtualization for Agile Data Delivery

Fast Data Strategy Houston Roadshow focused on the next industrial revolution on the horizon, driven by the application of big data, IoT and Cloud technologies. • Denodo’s innovative customer, Anadarko, elaborated on how data virtualization serves as the key component in their prescriptive and predictive analytics initiatives, driven by multi-structured data ranging from customer data to equipment data. • Denodo’s session, Unleashing the Power of Data, described the complexity of the modern data ecosystem and how to overcome challenges and successfully harness insights. • Our Partner Noah Consulting, an expert analytics solutions provider in the energy industry, explained how your peers are innovating using new business models and reducing cost in areas such as Asset Management and Operations by leveraging Data Virtualization and Prescriptive and Predictive Analytics. For more information on upcoming roadshows near you, follow this link: https://goo.gl/WBDHiE

Fast Data Strategy Houston Roadshow Presentation

Building a Single Logical Data Lake: For Advanced Analytics, Data Science, an...

Watch full webinar here: https://bit.ly/3dudL6u It's not if you move to the cloud, but when. Most organisations are well underway with migrating applications and data to the cloud. In fact, most organisations - whether they realise it or not - have a multi-cloud strategy. Single, hybrid, or multi-cloud…the potential benefits are huge - flexibility, agility, cost savings, scaling on-demand, etc. However, the challenges can be just as large and daunting. A poorly managed migration to the cloud can leave users frustrated at their inability to get to the data that they need and IT scrambling to cobble together a solution. In this session, we will look at the challenges facing data management teams as they migrate to cloud and multi-cloud architectures. We will show how the Denodo Platform can: - Reduce the risk and minimise the disruption of migrating to the cloud. - Make it easier and quicker for users to find the data that they need - wherever it is located. - Provide a uniform security layer that spans hybrid and multi-cloud environments.

Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)

Unlocking Big Data Silos in the Enterprise or the Cloud (Con7877)

Watch full webinar here: https://bit.ly/32TT2Uu Data virtualization is not just for self-service, it’s also a first-class citizen when it comes to modern data platform architectures. Technology has forced many businesses to rethink their delivery models. Startups emerged, leveraging the internet and mobile technology to better meet customer needs (like Amazon and Lyft), disrupting entire categories of business, and grew to dominate their categories. Schedule a complimentary Data Virtualization Discovery Session with g2o. Traditional companies are still struggling to meet rising customer expectations. During this webinar with the experts from g2o and Denodo we covered the following: - How modern data platforms enable businesses to address these new customer expectation - How you can drive value from your investment in a data platform now - How you can use data virtualization to enable multi-cloud strategies Leveraging the strategy insights of g2o and the power of the Denodo platform, companies do not need to undergo the costly removal and replacement of legacy systems to modernize their systems. g2o and Denodo can provide a strategy to create a modern data architecture within a company’s existing infrastructure.

Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...

Watch full webinar here: https://bit.ly/3rwWhyv The Data Mesh architectural design was first proposed in 2019 by Zhamak Dehghani, principal technology consultant at Thoughtworks, a technology company that is closely associated with the development of distributed agile methodology. A data mesh is a distributed, de-centralized data infrastructure in which multiple autonomous domains manage and expose their own data, called “data products,” to the rest of the organization. Organizations leverage data mesh architecture when they experience shortcomings in highly centralized architectures, such as the lack domain-specific expertise in data teams, the inflexibility of centralized data repositories in meeting the specific needs of different departments within large organizations, and the slow nature of centralized data infrastructures in provisioning data and responding to changes. In this session, Pablo Alvarez, Global Director of Product Management at Denodo, explains how data virtualization is your best bet for implementing an effective data mesh architecture. You will learn: - How data mesh architecture not only enables better performance and agility, but also self-service data access - The requirements for “data products” in the data mesh world, and how data virtualization supports them - How data virtualization enables domains in a data mesh to be truly autonomous - Why a data lake is not automatically a data mesh - How to implement a simple, functional data mesh architecture using data virtualization

Enabling a Data Mesh Architecture with Data Virtualization

Reinvent Your Data Management Strategy for Successful Digital Transformation

Watch full webinar here: https://bit.ly/3FHKalT Given the growing demand for analytics and the need for organizations to advance beyond dashboards to self-service analytics and more sophisticated algorithms like machine learning (ML), enterprises are moving towards a unified environment for data and analytics. What is the best approach to accomplish this unification? In TDWI’s recent Best Practice Report, Unified Platforms for Modern Analytics, written by Fern Halper, TDWI VP Research, Senior Research Director for Advanced Analytics, adoption, use, challenges, architectures, and best practices for unified platforms for modern analytics is explored. One of the approaches for unification outlined in the report is a data fabric approach. Join us for a webinar with our Director of Product Marketing, Robin Tandon, where he will discuss the role of the logical data fabric in a unified platform for modern analytics, focusing on several of the key findings outlined in this report. He will share insights and use case examples that demonstrate how a properly implemented logical data fabric is the most suitable approach for Unified Data Platforms across enterprises and organizations. Watch on-demand & Learn: - The benefits of a unified platform and its ability to capture diverse & emerging data types and how to support high performance and scalable solutions. - The role of an enhanced AI driven data catalog and its implications towards the findings in the best practice report. - Implications of a logical data fabric as it relates to several of the recommendations outlined in the report.

The Role of the Logical Data Fabric in a Unified Platform for Modern Analytics

The data services marketplace is enabled by a data abstraction layer that supports rapid development of operational applications and single data view portals. In this presentation yo will learn services-based reference architecture, modality, and latency of data access. - Reference architecture for enterprise data services marketplace - Modality and latency of data access - Customer use cases and demo This presentation is part of the Denodo Educational Seminar , and you can watch the video here goo.gl/vycYmZ.

Data Services Marketplace

Watch full webinar here: [https://buff.ly/2sLhFAc] TransAlta is an electric power generator company headquartered in Calgary, Alberta. TransAlta's IT department initiated "Zero Data Center" project to move their entire data layer to the cloud for flexibility, agility and lower TCO. Data virtualization technology played a central role in TransAlta's real-time data integration, while helping them move to the cloud with zero down-time Attend this Denodo DataFest 2018 session to learn: Who is TransAlta and why TransAlta wanted to move their entire enterprise data layer to the cloud Why data virtualization played a critical role in TransAlta's cloud modernization effort How TransAlta uses DV in their energy trading, wind icing forecast and HR fuctions

Cloud Modernization with Data Virtualization

Watch this webinar in full here: https://buff.ly/2IxM8Iy Watch all webinars from the Denodo Packed Lunch webinar series here: https://buff.ly/2IR3q6w While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best of breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform and provide real-time data integration, while delivering self-service data platform to business users. Attend this session to learn how big data fabric enabled by data virtualization: • Provides lightning fast self-service data access to business users • Centralizes data security, governance and data privacy • Fulfills the promise of data lakes to provide actionable insights

What is cloud data management

Solix Technologies, Inc

Big Data Fabric: A Necessity For Any Successful Big Data Initiative

A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020. Abstract: The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability. At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh. The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership. This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.

Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...

Dr. Arif Wider

This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems. Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/) Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.

Data Mesh Part 4 Monolith to Mesh

Tendances (20)

Stream based Data Integration

Denodo’s Data Catalog: Bridging the Gap between Data and Business (APAC)

Journey to Big Data: Main Issues, Solutions, Benefits

Flash session -streaming--ses1243-lon

Organising the Data Lake - Information Management in a Big Data World

Modernizing Data Architecture using Data Virtualization for Agile Data Delivery

Fast Data Strategy Houston Roadshow Presentation

Building a Single Logical Data Lake: For Advanced Analytics, Data Science, an...

Simplifying Your Cloud Architecture with a Logical Data Fabric (APAC)

Unlocking Big Data Silos in the Enterprise or the Cloud (Con7877)

Self Service Analytics and a Modern Data Architecture with Data Virtualizatio...

Enabling a Data Mesh Architecture with Data Virtualization

Reinvent Your Data Management Strategy for Successful Digital Transformation

The Role of the Logical Data Fabric in a Unified Platform for Modern Analytics

Data Services Marketplace

Cloud Modernization with Data Virtualization

What is cloud data management

Big Data Fabric: A Necessity For Any Successful Big Data Initiative

Data Mesh in Practice - How Europe's Leading Online Platform for Fashion Goes...

Data Mesh Part 4 Monolith to Mesh

Similaire à Global databases on the example of Betfair company

Oracle databáze – Konsolidovaná Data Management Platforma

Oracle databáze - zkonsolidovat, ochránit a ještě ušetřit! (1. část)

Jak konsolidovat Vaše databáze s využitím Cloud služeb?

Watch the full session: Denodo DataFest 2016 sessions: https://goo.gl/DOrhiA Connected use cases are gaining momentum! Data integration is the foundation for enabling these connections. In this session, you will experience first-hand our customer case studies and implementation architectures of IoT solutions. In this session, you will learn: • The role of data virtualization in enabling IoT use cases • How our customers have successfully implemented IoT solutions using data virtualization • How our product complements other IoT technologies This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6

Denodo DataFest 2016: The Role of Data Virtualization in IoT Integration

The Data World Distilled Understanding how the data world works in the Big Data era I created this slide deck as a learning tool for new employees, I figured I would post it in case it can help others understand the data space. This slide deck covers: - Big Data - Data Warehouses - ETL/Data Integration - Business Intelligence and Analytics - Data Quality - Data Testing - Data Governance It provides a brief description along with key vendors in the space.

the Data World Distilled

RTTS

Bestpeer++ a peer to-peer based large-scale data processing platform

Papitha Velumani

Big Data Companies and Apache Software

Bob Marcus

A5 oracle exadata-the game changer for online transaction processing data w...

Dr. Wilfred Lin (Ph.D.)

Seems MPPs (b)eat Hardware Strict DBs (Teradata/Greenplum) ?

ShivrajBiradar

ACDKOCHI19 - Next Generation Data Analytics Platform on AWS

AWS User Group Kochi

Automating Big Data with the Automic Hadoop Agent

CA | Automic Software

The Smarter Way To Manage Data

Smart ERP Solutions, Inc.

Watch full webinar here: https://bit.ly/3fpitC3 Enterprise organizations are shifting to self-service analytics as business users need real-time access to holistic and consistent views of data regardless of its location, source or type for arriving at critical decisions. Data Virtualization and Data Visualization work together through a universal semantic layer. Learn how they enable self-service data discovery and improve performance of your reports and dashboards. In this session, you will learn: - Challenges faced by business users - How data virtualization enables self-service analytics - Use case and lessons from customer success - Overview of the highlight features in Tableau

Accelerate Self-Service Analytics with Data Virtualization and Visualization

Watch full webinar here: https://bit.ly/3fBpO2M Data Fabric has been a hot topic in town and Gartner has termed it as one of the top strategic technology trends for 2022. Noticeably, many mid-to-large organizations are also starting to adopt this logical data fabric architecture while others are still curious about how it works. With a better understanding of data fabric, you will be able to architect a logical data fabric to enable agile data solutions that honor enterprise governance and security, support operations with automated recommendations, and ultimately, reduce the cost of maintaining hybrid environments. In this on-demand session, you will learn: - What is a data fabric? - How is a physical data fabric different from a logical data fabric? - Which one should you use and when? - What’s the underlying technology that makes up the data fabric? - Which companies are successfully using it and for what use case? - How can I get started and what are the best practices to avoid pitfalls?

Data Fabric - Why Should Organizations Implement a Logical and Not a Physical...

Life is a database. How you manage data defines business. ALTIBASE HDB with its Hybrid architecture combines the extreme speed of an In-Memory Database with the storage capacity of an On-Disk Database’ in a single unified engine. ALTIBASE® HDB™ is the only Hybrid DBMS in the industry that combines an in-memory DBMS with an on-disk DBMS, with a single uniform interface, enabling real-time access to large volumes of data, while simplifying and revolutionizing data processing. ALTIBASE XDB is the world’s fastest in-memory DBMS, featuring unprecedented high performance, and supports SQL-99 standard for wide applicability. Altibase is provider of In-Memory data solutions for real-time access, analysis and distribution of high volumes of data in mission-critical environments. Please visit our website (www.altibase.com) to learn more about our products and read more about our case studies. Or contact us at info@altibase.com. We look forward to helping you!

The Most Trusted In-Memory database in the world- Altibase

Altibase

Watch full webinar here: https://bit.ly/34iCruM Many organizations are embarking on strategically important journeys to embrace data and analytics. The goal can be to improve internal efficiencies, improve the customer experience, drive new business models and revenue streams, or – in the public sector – provide better services. All of these goals require empowering employees to act on data and analytics and to make data-driven decisions. However, getting data – the right data at the right time – to these employees is a huge challenge and traditional technologies and data architectures are simply not up to this task. This webinar will look at how organizations are using Data Virtualization to quickly and efficiently get data to the people that need it. Attend this session to learn: - The challenges organizations face when trying to get data to the business users in a timely manner - How Data Virtualization can accelerate time-to-value for an organization’s data assets - Examples of leading companies that used data virtualization to get the right data to the users at the right time

Bridging the Last Mile: Getting Data to the People Who Need It (APAC)

Times ten 18.1_overview_meetup

Byung Ho Lee

Exadata z pohledu zákazníka a novinky generace X8M - 1. část