データ仮想化とは ～ データ統合のための最先端ソリューションのご紹介（更新版）

Digital Transformation, even though a cliche, is definitely on top of every CEO's strategic initiative list. At the heart of any digital transformation, no matter the industry or the size of the company, there is an API strategy. Application programming interfaces (APIs) are the connection points between one application and another, and as such, they enable applications to build on each other, extend each other, and work with each other. Taken together, APIs represent a thriving ecosystem of developers that is showing no sign of slowing down.

Attend this webinar to learn:

- How data virtualization greatly enhances the capabilities of an API
- How data virtualization works as a service container, as a source for microservices and as an API gateway
- How data virtualization can create managed data services ecosystems in a thriving API economy

In an era increasingly dominated by advancements in cloud computing, AI and advanced analytics it may come as a shock that many organizations still rely on data architectures built before the turn of the century. But that scenario is rapidly changing with the increasing adoption of real-time data virtualization to provide a secure, logical data layer. No longer does disparate data sources have to be physically moved to a data warehouse and transformed before it can be used by the business.

Attend this session to learn:
* What is data virtualization
* How it differs from other enterprise data integration technologies
* Why data virtualization is increasingly finding enterprise-wide * deployment inside some of the largest organizations

Digital transformation, as cliché as it sounds, is on top of every decision maker’s strategic initiative list. And at the heart of any digital transformation, no matter the industry or the size of the company, there is an application programming interface (API) strategy. While API platforms enable companies to manage large numbers of APIs working in tandem, monitor their usage, and establish security between them, they are not optimized for data integration, so they cannot easily or quickly integrate large volumes of data between different systems. Data virtualization, however, can greatly enhance the capabilities of an API platform, increasing the benefits of an API-based architecture. With data virtualization as part of an API strategy, companies can streamline digital transformations of any size and scope.

Join us for this webinar to see these technologies in action in a demo and to get the answers to the following questions:

- How can data virtualization enhance the deployment and exposure of APIs?

- How does data virtualization work as a service container, as a source for microservices and as an API gateway?

- How can data virtualization create managed data services ecosystems in a thriving API economy?

- How are GetSmarter and others are leveraging data virtualization to facilitate API-based initiatives?

データ仮想化とは、どのようなソリューションなのか。昨今データ活用に注目が集まる中、データ統合や連携は重要な位置づけになりつつあります。データ仮想化は、データの物理的な複製なしでリアルタイムにデータ統合を実現できる、これまでとは全く異なる手法を採用するデータ統合戦略です。本ウェビナーでは、データ仮想化について、事例を交えてご紹介します。(本編は30分程度を予定しています。Q&Aのお時間も含めて1時間程度になります）

A successful data virtualization initiative bridges the gap between two very different perspectives of data management: IT and business.
However, most of the emphasis in these initiatives is put on the IT side, Modeling, performance, security, etc. Business users are often left with a large library of data sets, hard to use and navigate.

Denodo’s data catalog has been designed to cover the needs of those users and simplify the use and understanding of the virtual layer from the business perspective. It provides the extra capabilities required for self-service initiatives to succeed, while avoiding many of the common pitfalls of other cataloging solutions.

Attend this session to learn:

* The role of the data catalog in a logical architecture
* How to incorporate the data catalog in the life of “citizen analysts”
* Best practices in documentation and metadata management
* Advanced usage of Denodo’s data catalog

前回のデータ仮想化ソリューションのご紹介に続き、本ウェビナーでは世界トップクラスのデータ仮想化製品であるDenodoプラットフォームの開発・管理ツール（Virtual DataPort Administration Tool)と業務ユーザ向けのメタデータ/データ探索ツール（Data Catalog）の実機デモンストレーション、またデータ仮想化の開発・管理・運用のライフサイクルを完全にサポートする、以下の周辺機能をプレゼンテーションと実機デモンストレーションを交えてご紹介します。

・クエリ最適化（Cost Based Optimizer）
・キャッシュ機能
・並列分散処理基盤との連携による高速化
・ビルトイン監視ツール/外部監視ツールとの連携
・データガバナンスとデータ品質
・セキュリティ - LDAP/Active Directory連携
・機械学習・深層学習用Jupyter Notebook/Apache Zeppelinとの統合
・開発・運用のライフサイクル管理ツールであるソリューション・マネージャー
・ライセンスを一箇所で集中管理するライセンスマネージャー
・大規模開発でのバージョンコントロールシステムとの統合
・Webソースからのデータ取得を自動化する ITPilot
・EclipseプラグインDenodo4Eによるカスタムアプリケーション開発
※順番は前後する可能性があります

What started to evolve as the most agile and real-time enterprise data fabric, Data Virtualization is proving to go beyond its initial promise and is becoming one of the most important enterprise big data fabrics.

Attend this session to learn:

- What data virtualization really is
- How it differs from other enterprise data integration technologies
- Why data virtualization is finding enterprise wide deployment inside some of the largest organizations

"""By 2020, over 90% of Enterprises Will Use Multiple Cloud Services and Platforms""
IDC FutureScape: Worldwide Cloud 2018 Predictions

More and more organization are adopting multi-Cloud strategies to provide greater flexibility, cost savings, and performance optimization. Even when organizations commit to a single Cloud provider, they often have data and applications spread across different Cloud regions to support different business units or geographies. The result of this is a high distributed infrastructure that makes finding and accessing the data needed for reporting and analytics even more challenging.

Data Virtualization provides a data discovery and access layer that allows data users across the organization access the data that they need for their work - irrespective of whether the data is in a data center or in the Cloud - any Cloud! The Denodo Platform Multi-Location Architecture provides quick and easy managed access to data while still providing local control to the 'data owners' and complying with local privacy and data protection regulations (think GDPR and CCPA!).

In this webinar, you will learn about:

· The challenges facing organizations as the adopt multi-Cloud data strategies

· How the Denodo Platform provides a managed data access layer across the organization

· The different multi-location architectures that can maximize local control over data while still making it readily available

· How organizations have benefitted from using the Denodo Platform as a multi-Cloud data access layer

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Do you know the data warehouse/ business intelligence mission? Gartner says that it is “the analysis of all data from across the enterprise to answer questions about the past, present, and future.” That means, bringing together data from various locations – on premises, cloud, suppliers, and 3rd party –, in various formats – structured, unstructured, and semi-structured –, and across various latencies – batch, real-time, and streaming. The performance of BI tools tremendously suffers when they move large amounts of such data into their semantic layer in order to display charts and dashboards. So, how do you solve this problem?

That’s where data virtualization comes in as a solution. Data virtualization is a modern data integration technology that processes the queries at the sources and delivers only the results to the BI tools, thus dramatically improving the performance of these tools.

In this webinar, you will learn:
• Why the performance of BI tools suffers when accessing large amounts of disparate data.
• What is data virtualization and how it optimizes query processing, thus boosting BI performance.
• How to further use data virtualization as an universal semantic layer thus liberating business users to use any BI tools they like.

Digital transformation, the data economy, and becoming more data-driven are the current themes of boardroom discussions. Data is very valuable to organizations and their business users as long as it’s accessible, timely, consistent, trusted, adaptable and actionable, among a list of other things.

However, most organizations are dealing with data silos. Data is hidden inside databases, data warehouses, excel spreadsheets, and files; and, it’s stored on‐premises and in private and public clouds, often times across the globe. Therefore, it is not only time-consuming but also very costly to locate the required data, extract it from the system, integrate it, and turn it into meaningful, consistent and trusted information.

-How can you improve data delivery and extract value from your data?
-How can you make your data available and actionable in real-time?
-How are other organizations dealing with this data challenge?

In this webinar, we will explore data virtualization as the solution that fulfills all modern requirements for data delivery by looking at various customer case studies. Our speakers will discuss the challenges that hold organizations back from accessing their data and becoming data-driven. By taking you through real use cases, they will demonstrate how data virtualization has helped multiple organizations address their data challenges and create significant business benefits.

データ仮想化とは、どのようなソリューションなのか。昨今データ活用に注目が集まる中、データ統合や連携は重要な位置づけになりつつあります。データ仮想化は、データの物理的な複製なしでリアルタイムにデータ統合を実現できる、これまでとは全く異なる手法を採用するデータ統合戦略です。本ウェビナーでは、データ仮想化について、事例を交えてご紹介します。

Organizations are adopting cloud at a fast pace and migration of critical enterprise information resources could be a challenge when dealing with complex and big data landscape. Building the right data services architecture can help alleviate the pain points, whereby data virtualization comes to the rescue by enabling the companies to gain maximum benefits from cloud initiatives in form of agility, cost savings and more.

Attend this webinar to learn:

- How Denodo Platform's multi-location architecture can simplify and accelerate cloud migration.
- Best practices of deploying Denodo Platform in the cloud.
- Leverage Denodo's virtual data services layer to address and augment cloud solutions such as data warehouse modernization, data science, and data lakes in the cloud.
- Watch a demo showcasing data virtualization and analytics in the cloud.

Data lakes have grown to be a popular architecture that enables modern analytics and data science. However, complete replication of all corporate data into giant data lakes is unfeasible. Data volumes are too high, and replication to multiple systems creates brittle point-to-point connections. Out-of-synch data and uncontrolled replication leads to “data swamp” scenarios. On top of the physical data lake, a logical approach is more feasible: a logical layer that connects different systems (the data lake among them) and exposes them as one. The complexity of the back-end systems is hidden from the end user. Security, governance and auditing are again centralized.

As data volumes grow exponentially, optimization techniques have also evolved to perform in these scenarios. Techniques like complex query rewriting, on-the-fly data movement between sources, and MPP capabilities provide the processing muscle to perform efficiently.

Attend this session to learn:

* How a logical data lake can overcome some of the issues of data lakes
* How MPP acceleration and other optimization techniques designed for large data volumes work
* How Denodo customers have implemented logical data lakes to improve the value of their Hadoop investments

What makes data scientists happy? Of course data. They want it fast and flexible, and they want to do it themselves. But most classic data warehouses (DW) and data lakes are not easy to deal with for agile data access. A more practical solution is the logical data warehouse (LDW), which has shown to be a more agile foundation for delivering and transforming data and makes it easy to quickly plug in new data sources.

Attend this webinar to learn:

* How easily new data sources can be made available for analytics and data science
* How your organization can successfully migrate to a flexible LDW architecture in a step-by-step fashion
* How LDWs help integrate self-service analytics with classic forms of business intelligence

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spent most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.

Attend this webinar and learn:

* How data virtualization can accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
* How popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc. integrate with Denodo
* How you can use the Denodo Platform with large data volumes in an efficient way
* About the success McCormick has had as a result of seasoning the Machine Learning and Blockchain Landscape with data virtualization

Advanced data science techniques, such as machine learning, have proven to be extremely useful tools to derive valuable insights from existing data. However, they put the pressure on the data scientists to look for the right data and massage it into usable formats – a process that ends up consuming most of their time.

In this webinar, we want to discuss the use of data virtualization to obtain the information needed in a more efficient and agile manner, show you the value added by this technology via a predictive analytics demonstration, and finally present a customer success story of this use case.

Join the webinar to find out:

•How does data virtualization help data scientists accelerate data acquisition and preparation?

•How does the Denodo Platform for data virtualization integrate with popular tools from the data science ecosystem, like Spark, Python, Zeppelin, Jupyter, etc.?

•How can you use the Denodo Platform to deal with large volumes of data more efficiently?

•How is McCormick, a food flavoring giant, using data virtualization to season its machine learning and blockchain landscape?