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.

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?

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. An enterprise data model provides a common, well-understood classification of data.

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.

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

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

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

Conceptual Modeling Requires Conceptual and Critical Thinking

TDAN

I am surprised to see a lot of people jumping straight into logical or even physical modeling and skipping conceptual modeling. Don’t they understand the value of conceptual modeling? Don’t they understand the difference between the various levels of modeling? Or do they have cognitive limitations?

Convert From Big Data to Smart Data

TDAN

Did you know that 90% of all data has been generated over the last 2 years? Big Data has been an important topic in the marketing scene for quite some time.

Deep Learning Can Make a Difference

TDAN

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

Cloud Computing to Make Noise in 2020

TDAN

Some industry experts say that just a couple of years ago, cloud computing was dismissed as the latest technology trend, which was good for generating a lot of noise.

The Data-Centric Revolution: Lawyers, Guns and Money

TDAN

My book “The Data-Centric Revolution” will be out this summer. I will also be presenting at Dataversity’s Data Architecture Summit coming up in a few months. Both exercises reminded me that Data-Centric is not a simple technology upgrade.

Evolution of Data Management: The Role of Streaming Data and IoT Data Architecture

Cloudera

As the sources and speed of data capture grow, data management must evolve to keep up. But as data management evolves, what role will streaming data and IoT data architecture play? The Need for IoT Data Architecture That Delivers Real-Time Results.

We Need Data Ethics Now

TDAN

What are the ethics of collecting, managing, and analyzing data? Is it going to come to regulations enforced by government and industry consortiums to make businesses think about data ethics with the goal of truly treating data ethically?

Make an Impact: Find the Angry People

TDAN

Whenever I’m invited to a new organization to help with data challenges, I look for them. I love angry people. This may sound strange but bear with me. Here is the reason why angry people are great: They have opinions, and they aren’t afraid of sharing them.

The Non-Invasive Data Governance Framework – The Details

TDAN

The third and final part of the Non-Invasive Data Governance Framework details the breakdown of components by level, providing considerations for what must be included at the intersections.

The Difference Between Open Data and Public Data

TDAN

Is there a difference between open data and public data? There is a general consensus that when we talk about open data, we are referring to any piece of data or content that is free to access, use, reuse, and redistribute.

Zen and the Art of Data Maintenance: People Silos Cause Data Silos

TDAN

With the exponential growth of data from so many different sources, data silos (or in other words, separate unintegrated data stores) are more prevalent than ever. However, what is the root cause of data silos?

The Unfolding of the Data-Centric Paradigm – Part 1

TDAN

There is a movement to upend traditional thinking about information systems by putting data and meaning at the center of strategy, architecture, and system development sequencing. It is the most recent of a series of data-centric waves which, over several decades, have attempted to remedy the entrenched application-centric paradigm.

Considerations Before Adopting SaaS

TDAN

Software as a Service (SaaS) is becoming mainstream with a significant increase in both offerings and enterprise adoption. There are several advantages to SaaS – scalability, accessibility, and little to no Capex requirement, among others.

Data Professional Introspective: Why You Can’t Create an EDM Strategy

TDAN

Some countries successfully create long-term strategic plans, for examples China’s first 100-year plan was aimed at the elimination of extreme poverty by 2020. In 1980, there were 540 million people living in extreme poverty. By 2014, there were only 80 million.

Lean Data Governance Strategies

TDAN

The goal of data governance is to ensure the quality, availability, integrity, security, and usability within an organization. The way that you go about this is up to you.

Database Administration Impacted by the Connected Economy

TDAN

Before the end of the decade, the number of connected objects is projected to expand greatly. According to several different analysts, the number of connected objects by 2020 could be as low as 26 billion or as high as 50 billion. But even the low end of that range is quite large.

Employing IoT to Boost Business

TDAN

IoT has a lot more to offer than merely establishing connections between systems and devices. We are in the digital age that Hollywood once fancied with sophisticated connected devices and technologies surfacing day after day.

IoT 52

Cloud Computing for Startups

TDAN

In the wake of online security threats, more and more companies are turning to cloud computing in search of better protection. According to Forbes, 83% of enterprise workloads will be in the cloud by 2020.

Broken Data – What You Don’t Know Will Hurt You – Part 1

TDAN

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. Organizations typically define the scope of their data problems by their current (known) data quality issues (symptoms). However, this definition is […].

Barriers to Becoming an AI-Centric Company

TDAN

AI is a new buzzword in the corporate environment, and although 98% of companies are aiming to become data-driven, less than one third succeeded in 2018. There are multiple reasons behind this inability to adopt AI and data-driven approaches.

Principles for the Data-Centric Paradigm – Part 2

TDAN

There is a movement to upend traditional thinking about information systems by putting data and meaning at the center of strategy, architecture, and system development sequencing. Establishing a complete data-centric paradigm will require foundational principles which underscore the clear break with application-centric thinking, and which establish common ground on the unresolved issues inherited from the […].

The latest edition of The Data & Analytics Dictionary is now out

Peter James Thomas

After a hiatus of a few months, the latest version of the peterjamesthomas.com Data and Analytics Dictionary is now available. Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment.

Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Strengthen data security.

DAMA International Community Corner: Updates from DAMA-I

TDAN

We hope your Data Management career and programs are progressing well. If you have issues, please refer to DAMA.org for references, as well as the DAMA Data Management Body of Knowledge (DMBok). Good day from DAMA International.

Big Data Hadoop vs. Traditional RDBMS

TDAN

Apache Hadoop is a comprehensive ecosystem which now features many open source components that can fundamentally change an enterprise’s approach to storing, processing, and analyzing data.

Common Data Modeling Mistakes and Their Impact

TDAN

Although data modeling has been around for over 30 years, it ranks among the top areas from which database application problems arise. Today’s data modeling […].

Make an Impact: Data Governance and the Lost Art of Enterprise Architecture

TDAN

It seems like we’re so busy running that we no longer have time to think. We want to be faster and more responsive, but we aren’t even sure what we are trying to achieve. It’s like the person at your office that is always too busy, is working extra-long hours (and makes sure that everybody […].

Hadoop Security Basics (In Under 5 Minutes)

Dataiku

Between growing data and analytics teams, more collaborative projects, and GDPR , security and governance are becoming bigger issues. As organizations' analytical maturity improves, it's increasingly critical that business and technical users alike understand data best practices.

DB Pros Need to Know Cloud Migration

TDAN

In 1961, Professor John McCarthy was the first to publicly suggest in a speech at the centennial celebration of the Massachusetts Institute of Technology that: “Computing may someday be organized as a public utility just as the telephone system is a public utility.

Agile vs. Lean Project Management

TDAN

The perfect project management style has yet to be discovered. For the curious project owner, exploring all the different project management methodologies is an enriching endeavor.

Tales & Tips from the Trenches: How to Choose the Right Graph Database

TDAN

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Unicorns or Data Architects?

Dataiku

Data architects have a tendency to feel like unicorns: somehow they can manipulate data storage and computation structures like putty and also keep business objectives in mind. business Team data architecture communication

Essential Tips for Lean Startups

TDAN

Lean startups aren’t easy to run. They require a massive amount of time, energy, and dedication. Blood, sweat, and tears alone won’t cut it – lean startups must have a plan of action to thrive. What makes a lean startup success story? What makes lean startups fail?

Flexible and secure Data-as-a-Service delivered today

Birst BI

How many duplicated, dirty data pipelines are running throughout your organization? To put it simply, by setting up DaaS, Birst offers a better way to democratize data without sacrificing security, governance, and control. DaaS is a core component of modern data architecture.

Very Meta … Unlocking Data’s Potential with Metadata Management Solutions

erwin

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data.

Data-Driven Enterprise Architecture: Why Enterprise Architects Need to Look at Data First

erwin

It’s time to consider data-driven enterprise architecture. The traditional approach to enterprise architecture – the analysis, design, planning and implementation of IT capabilities for the successful execution of enterprise strategy – seems to be missing something … data.