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.

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.


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Creating an AI-Ready Data Architecture in the Cloud


But the data architectures that feed into them are just as vital. Sophisticated ML-as-a-service platforms such as Facebook’s FBLearner Flow are ideal for delivering AI-at-scale. Automation is what AI algorithms do best.

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

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.

The Difference Between Data Architecture and Enterprise Architecture


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 Movements in 2020


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

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?

Data Architecture and Design Thinking

Perficient Data & Analytics

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.

Data Architecture: 2.5 Types of Modern Data Integration Tools

Perficient Data & Analytics

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.

Data Professional Introspective: Data Architecture and the Role of Business


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

Data Architecture Crash Course: Key Terms


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?

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.

Trends in Enterprise Data Architecture and Model Deployment


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

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


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

Why Your Startup Needs Data Science


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 […].

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.

Three Key Takeaways from CDAO Europe 2019


‘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

Machine Learning Factors for Project Managers

The Data Administration Newsletter

Deploying a Machine Learning model to enhance the quality of your company’s analytics is going to take some effort: – To clean data– To clearly define objectives– To build strong project management Many articles have been […]. Machine learning model….

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.

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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.

Knowledge Graphs vs. Property Graphs – Part 1


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.

Agile Business Facilitated by Information Architecture & SAFe

The Data Administration Newsletter

This article attempts to analyze and make sense of a harmonization between Information Architecture and SAFe, and will address how their cooperation will contribute to the development of an Agile Business.

Data Management 20/20: Anatomy of a Business Glossary Definition


The business glossary is simple in concept, but it can be a challenge to structure, define and maintain shared business terminology. Consistent business meaning is important because distinctions between business terms are not typically well defined or documented.

Build an enterprise-ready, modern data architecture based on open source

IBM Big Data Hub

This isn’t surprising given the influx of multiple types of data from disparate sources and the popularity of open source methods to capture and turn it into insight Gartner analysts Merv Adrian and Donald Feinberg in a February 2018 report predict that “by 2022, more than 70 percent of new applications developed by corporate users will run on an open source database management system.”

Big Data’s Role in Improving Product Lifecycle Management

The Data Administration Newsletter

We’re living in a time where data is a crucial part of everything. quintillion bytes of data, and that number is only growing more extensive with the arrival of the Internet of Things. More importantly, this data doesn’t just stand still.

Data Management 20/20: The Unacceptable Cost of Bad Data – Part 1

The Data Administration Newsletter

“…quite simply, the better and more accessible the data is, the better the decisions you will make.” – “When Bad Data Happens to Good Companies,” ( The Business Impact of an organization’s Bad Data can cost up to 25% of the company’s Revenue (Ovum Research) Bad Data Costs the US healthcare $314 Billion. (IT

Knowledge Graphs vs. Property Graphs – Part II


Differences in Terminology and Capability Building on the terms and concepts introduced in Part I of this white paper, Part II digs deeper into the difference in the meaning of some key terms used in both Property Graphs and Knowledge Graphs, including LABELS, TYPES, and PROPERTIES.

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


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

What DBAs Should Do Before Taking a Vacation


Everybody wants to take a relaxing holiday from time to time, whether you are a veteran DBA standing watch over million dollar mission-critical database systems or a jack-of-all-trades who maintains all of your small organization’s SQL Servers, Windows Servers, and all of the other corporate IT assets.

Tales & Tips from the Trenches: Extend the Impact of Enterprise Data through Partnerships

The Data Administration Newsletter

A new approach to wicked problems is taking root: data-sharing partnerships that accelerate the innovation of solutions for shared problems.

Automating Your Corporate Data Estate


In the world of data, automation plays a well-honed role in rapidly developing modern data estates. Before we proceed any further, let’s establish an understanding about the purpose of a corporate data estate. Automation has revolutionized industries and business for years.

Are Your Data Skills Up to Date?

The Data Administration Newsletter

But as technology becomes more complex, the data that it mines and uses becomes more plentiful. These technologies collect, use, and report tons of data that help improve our daily […]. The information age has been upon us for most of the new millennium.

Partly Cloudy with a Scattered IT Environment

The Data Administration Newsletter

How many times, when you were a kid, did a thunderstorm cause an immediate mix of emotions: the fear of the continuous boom of the thunder as the clouds rolled in, the calming sensation of the smell of freshwater in the breeze and wind, and the awe and wonder as the lighting streaked through the […].

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The Data-Centric Revolution: Report From the Front Lines


Earlier this month we hosted the second annual Data-Centric Architecture Forum (#DCAF2020) in Fort Collins, CO. Last year, (2019) we hosted the first Data-Centric Architecture conference.

Everything is Big Data


The term “big data” has been bandied about for a number of years now, and it has gotten to the point where it has been used so much that it is a part of IT culture.

How to Develop a Sustainable Digital Platform


“The digital world is here but our old companies are simply not yet designed for digital.” Jeanne Ross (Designed for Digital) Your business may need to develop a new digital platform to replace your existing application-centric IT solution.

The Mainframe is a Modern Platform


Mainframes also can easily handle large amounts of data—multiple terabytes—such as is needed for analytical processing and machine learning. Indeed, the mainframe supports both traditional and modern applications and data management requirements, making it a key component of […].

Differences Between ‘Available’ and ‘Accessible’


A few months back, our company enjoyed a retreat a few hours north of the city. We bonded, brainstormed, and set visions and goals for the development of our company and our products. We also had bonfires with s’mores, and that’s more relevant than you might think.

Knowledge Graphs vs Property Graphs – Part III


Part 3 completes this article series by discussing some important topics beyond the critical differentiators in the terminology and capabilities of Property Graphs and Knowledge Graphs covered in Parts 1 and 2.

Storing Data in the Cloud

The Data Administration Newsletter

In the cloud-era, should you store your corporate data in Cosmos DB on Azure, Cloud Spanner on the Google Cloud Platform, or in the Amazon Quantum Ledger?

Introduction to Blockchain for DBAs


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