Archives: White Papers

Designing High-Performance Data Structures for Couchbase and MongoDB

New, business-transforming use cases often involve variable data feeds, real-time or near-time processing and analytics requirements, and the scale to process large volumes of data.

NoSQL databases, such as Couchbase and MongoDB, are purpose-built to handle the variety, velocity and volume of these new data use cases. Schema-less or dynamic schema capabilities, combined with increased processing speed and built-in scalability, make NoSQL the ideal platform.

But once we’ve agreed to make the move to NoSQL, the next step is to identify the architectural and technological implications facing the folks tasked with building and maintaining these new mission-critical data sources and the applications they feed.

As the data modeling industry leader, erwin has identified a critical success factor for the majority of organizations adopting a NoSQL platform like Couchbase or MongoDB.

Find out what the success factor is by downloading this technical white paper.

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Taking Control of NoSQL Databases

Data-driven businesses must adopt a new data modeling mindset

The digital world is moving faster than ever before, so the enterprise needs to keep pace by becoming data-driven.

That means using Big Data – much of it unstructured –  to effectively respond to customers, partners, suppliers and other parties in real time – and profit from those efforts.

NoSQL, and in particular the Couchbase and MongoDB platforms, is growing in adoption by organizations that are focused on supporting modern cloud applications and agile development.

If you’re considering the transition from traditional relational databases to NoSQL – or if you’re already using the technology – then you need to read our new e-book: Taking Control of NoSQL Databases.

We cover the rise of NoSQL, its vital role to data-driven organizations, and how it is changing the data modeling game.

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Data-Driven Business Transformation

Using data as a strategic asset and transformational tool to succeed in the digital age

Companies such as Airbnb, Amazon, Netflix and Uber have realized the value of data, harnessing it to create new business models, redefine and disrupt entire markets, and change the way customers think and therefore behave.

Known as data-driven enterprises, these organizations have transformed everything – how they make decisions, invent new products or services, and improve processes to add to both their top and bottom lines.

But digital transformation isn’t just about technology. It’s bigger than that – an organization’s culture, operations, business applications and content are all impacted. So then, how does an enterprise ensure that its digital transformation is successful? What’s the key?

The answer is data, or more specifically data management because what you do with your mission-critical information will determine your ability to achieve the desired results the C-suite wants to see.

By becoming part of your company’s DNA, data transforms everything …
Are you ready to seize the day – or should we say, seize the data and use it for competitive advantage and growth?

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Enterprise Architecture & Data Modeling

Enterprise Architecture & Data Modeling White Paper image

Practical steps to collect, connect and share your enterprise data for better business outcomes.

Effective data and enterprise architecture management is about enabling smarter business decisions; providing management access to the right information, in the right format, at the right time. In this white paper, you’ll discover how to:

  1. Adopt a business-outcome approach to enterprise architecture.
  2. Relate data and enterprise architecture to what the C-Suite really want.
  3. Build future-state models that secure senior management investment.
  4. Leverage data management to build architectures more quickly, manage data in context, and deliver information that management need.
  5. Deliver Digital Business improvements with enterprise and data architecture.
  6. Focus on outputs and audience to increase value to the organization.

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Enterprise Data Architecture and Data Governance: Use Metadata to Get to the Starting Gate

Instituting data governance within the organization will help ensure compliance with business policies, as well as reduce risks. But how does one get started with data governance?

In this white paper we explore some challenges in bootstrapping a data governance program and consider key methods for using metadata to establish the starting point for data governance. The paper focuses on how metadata management facilitates progress along three facets of the data governance program: assessment, collaboration, and operationalization.

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The Business Value of Data Modeling for Data Governance

Data governance works best when it’s strongly aligned with the drivers, motivations, and goals of the business. But given that data can be a technical discipline, it’s often difficult to find a way to translate the technical data environment into an easy-to-understand format that uses business terminology.

Whether you are a businessperson looking to understand how to make data governance work for you, or a data management professional trying to communicate better with your business sponsors, this white paper offers practical, real-world guidance on how to better align data governance with business goals.

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Operationalizing Data Governance with Living Metadata

With any metadata project, it is critical to recognize that as the business transforms, the data and metadata must continually be updated and reviewed to ensure it continues to be useful.

In this white paper we explore best practices in maintaining a “living” metadata management platform. We also cover the key factors in ensuring timeliness and utility of an enterprise metadata resource and how collaboration and utilization enhance data governance and stewardship.

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The Role of Metadata in a Data Governance Strategy

As the interest in managing information and enforcing corporate data management policies increases, data governance programs to manage data sets are becoming more and more vital to the business operation. However, in this rush for data governance programs, sometimes the true utility and importance of metadata can be missed.

In this white paper, David Loshin of Knowledge Integrity, Inc. discusses the importance of data governance and the role of metadata management as a way to empower data governance and enforce data policies.

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