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）

成功するデータ仮想化イニシアチブは、ITとビジネスの間にあるデータ管理に対する非常に異なる視点のギャップを埋めています。ただし、重点の多くはIT側、すなわち、モデリング、パフォーマンス、セキュリティなどに置かれています。多くの場合、ビジネスユーザーは使用や閲覧が困難なデータセットの大きなライブラリセットを目の当たりにしています。Denodoのデータカタログはこうしたユーザーのニーズをカバーし、ビジネスの観点から仮想レイヤーの使用と理解をシンプルにするように設計されています。これはセルフサービスイニシアチブが成功するために必要な追加機能を提供すると同時に、他のカタログソリューションの一般的な落とし穴の多くを回避します。

本ウェビナーでは、

・論理アーキテクチャでのデータカタログの役割
・”シチズンアナリスト”の生活にデータカタログを取り込む方法
・ドキュメントおよびメタデータ管理のベストプラクティス
・Denodoのデータカタログの高度な使用方法

について理解できます。

Most people associate data virtualization with BI and analytics. However, one of the core ideas behind data virtualization is the decoupling of the consumption method from the data model. Why should the need for data requests in JSON over HTTP require extra development? Denodo provides immediate access to its datasets via REST, OData 4, GeoJSON and other protocols, with no coding involved. Easy to scale, cloud friendly and ready to integrate with API management tools, Denodo can be the perfect tool to fulfill your API strategy!

Attend this session to learn:

What’s the role of Denodo in an API strategy
Integration between Denodo and other elements of the API stack, like API management tools
How easy is to access Denodo as a RESTful endpoint
Advanced options of Denodo web services: OAuth, OpenAPI, geographical capabilities, etc.

An eclectic mix of old and new data drives every decision and every interaction, but too many organisations are attempting unsuccessfully to consolidate this data into a single repository which is time-consuming, resource-intensive, expensive, and risky.

Join this Denodo and HCL Webinar to discover how data virtualization provides an effective modern day architecture and an alternative to data consolidation and the challenges of fragmented data ecosystems and traditional integration approaches. We will share stories and provide multiple perspectives on best practices and solutions.

Content will include:
• Business use cases that highlight challenges and solutions that result in faster time-to-market and greater ROI.
• Suggested approaches to achieve extreme agility for competitive advantage.

If you are a BI or Analytics Manager, Data or Enterprise Architect, Cloud Architect, Data Manager, Data Scientist, CIO, CDO, CFO or anyone who manages data and its use, then this event will be of value to you.

注目されるデータレイクですが、これはデータサイエンティストなどが様々なデータを物理的に複製したデータストレージプラットフォームとして構築されてきました。しかし昨今ではビッグデータプライバシールールであったり、データを扱う部門の制限であったりと中中型データリポジトリアプローチが難しいものとなってきました。そこでデータ仮想化を使用すると、物理的複製の必要なく、すべてのデータを論理的かつ仮想的なデータレイクを構築することが可能となります。
本ウェビナーでは以下について触れる予定です。
・物理的なデータレイクの制限
・データサイエンティストだけでなく、すべてのユーザ向けに論理データレイクを構築する方法
・論理データレイクが必要な新しいユースケース

プレゼンテーション:30分、デモ:15分、Q&A:15分程度を予定しております。

'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 benefited from using the Denodo Platform as a multi-Cloud data access layer

The use of Data Virtualization as a global delivery layer means that Denodo is a critical component of the data architecture. It cannot fail, needs to be fault tolerant and perform as designed. In this context, enterprise level-monitoring is key to make sure the virtual layer is in good health and proactively detect potential issues. Fortunately, Denodo provides a full suite of monitoring capabilities and integrates with leading monitoring tools like Splunk, Elastic and CloudWatch.

Attend this session to learn:

How to configure the key global parameters of the Denodo server
How to integrate Denodo with enterprise monitoring solutions like Splunk and Cloudwatch
Key metrics to monitor

デジタルトランスフォーメーション、データエコノミー、そしてデータ駆動型組織になることは、現在の経営テーマの１つです。データは、アクセスしやすく、タイムリーで、一貫性があり、信頼でき、適応性があり、実用的である限り、組織とそのビジネスユーザーにとって非常に貴重です。
しかし、ほとんどの組織ではデータがサイロ化され、データベース、データウェアハウス、Excelスプレッドシート、およびファイル類に隠され、またオンプレミスおよびプライベートクラウドやパブリッククラウドに格納され多くは世界中に分散されています。
それゆえ、必要なデータを見つけてシステムから抽出し、統合し、意味のある一貫した信頼できる情報に変換することは、時間がかかるだけでなく非常にコストがかかります。
このウェビナーでは、さまざまなお客様のケーススタディを見て、データ配信に関する最新要件を満たすソリューションとしてのデータ仮想化についてご案内します。
（プレゼンテーション30分程度、デモ10分程度、QA10分程度を予定しております）

Historically data lakes have been created as centralized physical data storage platform for data scientists to analyze data. But lately the explosion of big data, data privacy rules, departmental restrictions among many other things have made the centralized data repository approach less feasible. In his whitepaper, renowned analyst Rick F. Van Der Lans talks about why decentralized multi purpose data lakes are the future of data analysis for a broad range of business users.

Please attend this session to learn:
- The restrictions of physical single purpose data lakes
- How to build a logical multi purpose data lake for business users
- The newer use cases that makes multi purpose data lakes a necessity

Historically data lakes have been created as centralized physical data storage platform for data scientists to analyze data. But lately the explosion of big data, data privacy rules, departmental restrictions among many other things have made the centralized data repository approach less feasible. Using Data Virtualization allows organizations to create a logical - or virtual data lake - without having to physically copy and centralize all of their data.

Attend this session to learn:
The restrictions of physical single purpose data lakes
How to build a logical data lake for all users - not just for data scientists
The newer use cases that makes logical data lakes a necessity

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