Five Modern Data Architecture Trends

David Menninger's Analyst Perspectives

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data.

Building a Modern Data Architecture for the 2020s

DataKitchen

The post Building a Modern Data Architecture for the 2020s first appeared on DataKitchen. News News / PR

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DataOps: The Foundation for Your Agile Data Architecture

DataKitchen

Learn about four data architectures patterns for agility - DataOps, Data Fabric, Data Mesh & Functional Data Engineering - & an example combining all four. The post DataOps: The Foundation for Your Agile Data Architecture first appeared on DataKitchen.

How to build a successful cloud data architecture

DataKitchen

The post How to build a successful cloud data architecture first appeared on DataKitchen. News News / PR

The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

A next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.

Data Minimization as Design Guideline for New Data Architectures

Data Virtualization

IT excels in copying data. It is well known organizations are storing data in volumes that continue to grow. However, most of this data is not new or original, much of it is copied data. For example, data about a.

Modernizing Data Architectures

Data Virtualization

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

How Do You Design New Data Architectures?

Data Virtualization

Organizations are rethinking their current data architectures. Business Data Architecture Data storage data stores data virtualization ETL Modern Data Architecture Snowflake SQL technology

Data Architecture Movements in 2020

TDAN

Data is commonly referred to as the new oil, a resource so immensely powerful that its true potential is yet to be discovered.

The Difference Between Data Architecture and Enterprise Architecture

erwin

Although there is some crossover, there are stark differences between data architecture and enterprise architecture (EA). That’s because data architecture is actually an offshoot of enterprise architecture. The Value of Data Architecture.

Data Architecture 101: Ensuring Scalability & Security

Dataiku

Data architecture is an umbrella term that encompasses data storage , computational resources, and everything in between. All the technology that supports the collection, processing, and dashboarding of data is included in the architecture.

The Unexpected Cost of Data Copies

This paper will discuss why organizations frequently end up with multiple data copies and how a secure "no-copy" data strategy enabled by the Dremio data lake service can help reduce complexity, boost efficiency, and dramatically reduce costs.

Critical Components of Big Data Architecture for a Translation Company

Smart Data Collective

Big data technology has been instrumental in helping organizations translate between different languages. We covered the benefits of using machine learning and other big data tools in translations in the past. How Does Big Data Architecture Fit with a Translation Company?

New Data Architectures are too Data-Store-Centric

Data Virtualization

Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly.

Data Professional Introspective: Data Architecture and the Role of Business

TDAN

The phrase “data architecture” often has different connotations across an organization depending on where their job role is. For instance, most of my earlier career roles were within IT, though throughout the last decade or so, has been primarily working with business line staff. When I present at conferences, seminars, or DAMA chapters, I ask […].

Top 7 characteristics of a modern data architecture

IBM Big Data Hub

A modern data architecture (MDA) must support the next generation cognitive enterprise which is characterized by the ability to fully exploit data using exponential technologies like pervasive artificial intelligence (AI) , automation, Internet of Things (IoT) and blockchain

Responsibility of Data Architecture in Data Governance

Perficient Data & Analytics

The data architecture capability will supply the components and standards necessary to implement other capabilities coherently and enable them to work together. A primary responsibility of data architecture is to define and have an accepted enterprise-wide set of models, standards, glossaries and hierarchies which allow a standard description of data across business lines, products and functional areas.

Checklist Report: Preparing for the Next-Generation Cloud Data Architecture

Data architectures have evolved dramatically. It is time to reconsider the fundamental ways that information is accumulated, managed, and then provisioned to the different downstream data consumers.

How to Develop the Essential Data Architecture for Your Digital Transformation Strategy

TreehouseTechGroup

On the other hand, any business that does… The post How to Develop the Essential Data Architecture for Your Digital Transformation Strategy appeared first on Treehouse Tech Group. Data Strategy Digital Transformation

Trends in Enterprise Data Architecture and Model Deployment

Dataiku

The goal of this survey was to uncover trends in data architecture in the enterprise, specifically in the context of operationalizing machine learning models.

Data Architecture Crash Course: Key Terms

Dataiku

We’ve set out to demystify the jargon surrounding data architecture to enable every team to understand how it impacts their objectives. Hadoop Enterprise Ai Data Transformation data architectureNot sure what Hadoop actually is? A little fuzzy on what the difference is between cloud and on-prem storage?

Data Architecture and Design Thinking

Perficient

Simplicity is a very important strategy as people are thinking of designing their modern data platforms. Design is often a complex task, so I recommend applying strong design thinking to simple goals as you lead your data architecture teams. I have stood before many architecture review boards (ARB) for organizations and found that many teams over complicate things. Break down this architecture into smaller components and release frequently.

How to Democratize Data Across Your Organization Using a Semantic Layer

Speaker: speakers from Verizon, Snowflake, Affinity Federal Credit Union, EverQuote, and AtScale

Learn from data and analytics leaders at Verizon, Snowflake, EverQuote, and Affinity Federal Credit Union about how to foster a data literate culture while scaling data access and self-service analysis across your organization using a semantic layer.

Data Architecture: 2.5 Types of Modern Data Integration Tools

Perficient

As we move into the modern cloud data architecture era, enterprises are deploying 2 primary classes of data integration tools to handle the traditional ETL and ELT use cases. The first type of Data integration tools are GUI-Based Data Integration solutions.

Converting Big Data into Actionable Intelligence

The Data Administration Newsletter

In today’s world, access to data is no longer a problem. There are such huge volumes of data generated in real-time that several businesses don’t know what to do with all of it. Unless big data is converted to actionable insights, there is nothing much an enterprise can do.

Metadata Improves Security, Quality, and Transparency

The Data Administration Newsletter

They use data better. How does Spotify win against a competitor like Apple? Using machine learning and AI, Spotify creates value for their users by providing a more personalized experience.

Analytics as a Service (AaaS)

The Data Administration Newsletter

As technology is improving itself with continuous upgrades, it has led to the birth of using software without installing it on your device, such service is known as Software as a Service (SaaS).

None Shall Pass! Are Your Database Standards Too Rigid?

The Data Administration Newsletter

Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard. I guess I should quickly define what I mean by a “database standard” for those who are not aware.

The Changing Database Landscape

The Data Administration Newsletter

When you’ve been involved in data management for as long as I have, things are definitely bound to change. And things have changed, quite a lot, in fact.

DAMA International Community Corner: August 2021 – A Wrap for Now

The Data Administration Newsletter

It has been an incredible run. I hope it is just “see you soon” rather than “goodbye.” With this column, DAMA International’s streak of quarterly columns since mid-2001 is coming to an end. The columns have featured the activities and incredible work of DAMA International over the past two decades.

Business Pace Contributes to Data Challenges

The Data Administration Newsletter

The increasing speed and pace of business certainly contributes to several data challenges (quality, timeliness, availability and, most important, usability of the data).

Big Data Modeling Improves Business Intelligence

The Data Administration Newsletter

Through big data modeling, data-driven organizations can better understand and manage the complexities of big data, improve business intelligence (BI), and enable organizations to benefit from actionable insight.

Why Your Startup Needs Data Science

TDAN

Top-quality data currently represents one of the most important resources for any company. Startups that lack familiarity with important tendencies and trends in their industry need to have this crucial data […].

Tales & Tips from the Trenches: Demystifying Edge Computing

The Data Administration Newsletter

With increasing number of Internet of Things (IoT) getting connected and the ongoing boom in Artificial Intelligence (AI), Machine Learning (ML), Human Language Technologies (HLT) and other similar technologies, comes the demanding need for robust and secure data management in terms of data processing, data handling, data privacy, and data security.

Have We Forgotten the Purpose of Technology in Business?

The Data Administration Newsletter

Fundamentally, the purpose of technology in business is to manage the treasure trove of data captured within sophisticated technological systems. We do this to understand and communicate with the world we see around us and help us better engage with that world to become more successful.

Three Key Takeaways from CDAO Europe 2019

Corinium

‘Ethics’, ‘strategy’ and ‘collaboration’ were the words on everyone’s lips when 115 data and analytics leaders descended on Berlin for CDAO Europe 2019 last week. Data Strategy Data Ethics Data Architecture

The Data-Centric Revolution: Fighting Class Proliferation

The Data Administration Newsletter

One of the ideas we promote is elegance in the core data model in a Data-Centric enterprise. Look at most application-centric data models: you would think they would be simpler than the enterprise model, after all, they are a small subset of it.

Is Artificial Intelligence a Problem or an Opportunity?

The Data Administration Newsletter

Artificial Intelligence (AI) seems to have reached its peak, and yet it is still growing and reaching even the most remote parts of the world. There are countless benefits to this technology, including life-saving tools and systems that function with automated AI algorithms.

Data Gravity and Cloud Computing

The Data Administration Newsletter

Cloud computing is growing rapidly as a deployment platform for IT infrastructure because it can offer significant benefits. But cloud computing is not always the answer, nor will it replace all of our on-prem computing systems anytime soon—no matter what the pundits are saying.

Technologies that Could See Significant Growth

The Data Administration Newsletter

While we have seen a change in the calendar year, one initiative that continues to be a top priority for businesses is storing, managing, accessing and optimizing corporate data. With the new year events well behind us, we’re steadily focused on moving forward in 2021.

Knowledge Graphs vs. Property Graphs – Part 1

TDAN

Flexibility is one strong driver: heterogeneous data, integrating new data sources, and analytics all require flexibility. We are in the era of graphs. Graphs are hot.

The Data-Centric Revolution: Data-Centric vs. Centralization

TDAN

They had seemingly achieved many of the benefits of becoming data-centric through decentralization: all […].

The Lifecycle of Data

The Data Administration Newsletter

Most data is not static. No, data has a life in which it changes, is used for perhaps multiple purposes, and gets moved all over the place. So, it makes sense to think about the lifecycle of your data at your organization.