Learn about the latest in Data Management from our experts

Events

The Data Leadership Series – A festive fireside splat (on-demand)

We are rounding up the major events in the world of data in 2023 and look ahead to 2024.

We’ll share our reflections on the ever-growing data landscape and look back on some of the challenges and highlights from the past year, and indulge our curiosity as we make some predictions for the next 12 months.

The Data Leadership Series – Making sense of AI (on-demand)

AI is transforming industries, and with the emergence of models like ChatGPT & Bard, business & tech leaders are eager to adapt. At our event, we’ll explore the world of “generative” and “predictive” AI, delve into crucial business outcomes, establish governance frameworks, and spotlight significant use cases that are reaping benefits at an unprecedented scale.

The Data Leadership Series – Demystifying data products (on-demand)

A Data Product is a way to make a data asset reusable and consumable. It is an idea that combines data management with product thinking but there is a lot of confusion about what it is or what it should be. We hope to provide some context to this debate and share some useful insights for Data Leaders who are reflecting on this topic.

The Data Leadership Series – Building an effective data culture (on-demand)

An effective data culture will largely influence the successful outcome of your data strategy. As a data leader, often fighting for room to operate in an organisational culture that can be resistant to change, you need some ways to communicate how embracing data as a positive and progressive force will ultimately accelerate not just your success, but your stakeholders’ success too.

The Data Leadership Series – Choosing an operating model (on-demand)

An Operating Model for enterprise data management refers to the framework and processing put into place to efficiently manage and utilise data across your organisation. You will learn about how to approach selecting the right operating model, the key concepts underpinning an operating model and the steps in creating successful ways of working for data.

The Data Leadership Series – Designing a data strategy (on-demand)

We introduce the approach, principles and deliverables necessary for you to understand how to design an impactful data strategy. This is particularly useful for CDAOs and data teams looking for guidance on bringing their colleagues into the fold – by defining a data strategy that delivers commercial outcomes.

Articles

How to make your M&A Data Migration a success

Migrating data from one organisation to another is one of the toughest challenges a Data Leader will face. It’s a complex process, and by the end of it you want single landscape with data you can trust. In this article we discuss how to make your data migration a success.

How to build trust in your data

If you want to use your data to make business decisions, you need to be able to trust it. Using a framework like DCAM is one of the best ways to achieve that. This article discusses the different aspects to consider, the traps to avoid and the benefits of doing it right.

Data trends to watch for in 2024

What will 2024 bring? If AI is here to stay, it’s time to focus on Data Governance and Data Fluency – because clean data is more important than ever.

Data trends that shaped 2023

2023 was a busy one in the world of data, with the rise of AI, new concepts like Data Products, and challenges to the way Data & Analytics teams prove their value. 

Are you ready for AI?

AI is transforming businesses rapidly. It’s crucial to balance innovation with risk management and adopt AI responsibly.

Harnessing AI starts with data capabilities

AI’s success relies on robust data management. Frameworks like DCAM & CDMC ensure effective AI in finance, healthcare, and beyond.

Data product supply chains – an enterprise view

Organisations navigate complex data environments, with Data Leaders leveraging data products for utility, quality & convenience in the Data Product Lifecycle.

The rise of data products

Data Leaders debate managing data as a product. Embracing this shift can fuel product development, with engagement, assessment, and robust frameworks being key.

Can Organisational Culture Disincentivise Data Culture?

Data culture, while influenced by organisational culture, is a unique concept sometimes dismissed as immeasurable. Evaluating your data culture and its daily application can enhance workforce engagement as it develops.

Data Culture: A Vicious Cycle or Virtuous Circle?

Data culture refers to the consistent thought patterns and behaviours employees demonstrate while handling data, with the key aspect being the ‘repeated patterns’ in data interaction.

Building a data operating model

If your Data Strategy is the map, your Operating Model is the vehicle that will get you to your destination. It defines the people and ownership, governance, processes and tooling needed to operate your Data & Analytics Management function. Discover the guardrails, operating levels and accountabilities it should contain.

Making your data strategy investable

Discover how to align your data strategy with business objectives, engage stakeholders, and drive value. This article guides you in transforming your data strategy from a technical document into a dynamic business tool that delivers a return on investment.

Designing a data strategy

Aligning your data strategy with overall objectives is critical. Treating it as a living document, adaptable to changing conditions, is key to achieving measurable progress and delivering on organisational goals.

CASE STUDIES

Using Solidatus for Policy Compliance and Management

We have been helping a US-based Global Systemically Important Bank (G-Sib) align a data policy update to a defined set of data management capabilities. Read about how we used Solidatus to map DCAM into the organisation’s data fabric to create a formal evidence-based mechanism to monitor policy compliance.

Using Solidatus for ESG Reporting

We’ve been working with a global luxury goods company to help them streamline and automate their Climate Report, part of their ESG (Environmental, Social & Governance) reporting suite. Learn how we used Solidatus to map information about greenhouse gas emissions, water use and waste from 450 sites.

Data Products & Ownership

We have been designing a Data Management Operating Model for an International Asset Management Company who were introducing data products into their data estate and struggling to define data ownership. Read about how we customised our best practice framework to design a solution for them.

Papers

Data Leaders’ Guide to Implementing DCAM

Are you a Data Leader with a data landscape you don’t fully understand? This guide describes DCAM and how to use it to set your goals, assess your capabilities, establish your targets, define your roadmap and then implement your plans. With plenty of tips and stories from Pete and Mark.

Making sense of AI

AI is revolutionising the professional world, from automating fraud detection in banking to developing new treatments in pharmaceuticals and explaining credit denials via GANs. While it reshapes business operations and roles, this transformation brings inherent risks alongside its benefits.

7 avoidable mistakes with data products

A data product makes a data asset reusable and consumable. Data assets can be datasets, dashboards, machine-learning models and more. Here are some of the pitfalls you should consider when building data products.

Anatomy of a Data Culture

A good data culture is one where everyone feels a collective responsibility for data, and interacting with it is a normal part of everyday work. But how to encourage the right attitudes and behaviours? Our guide serves as a roadmap for organisations aiming to embed a data-driven mindset at every level.

Anatomy of a Data Operating Model

A Data Operating Model can be thought of as a series of models that address the different aspects that need to be defined – like governance, infrastructure and funding – plus of course some metrics so you can measure its success. This is our view of the eight essential elements a good Data Op Model should have.

Anatomy of a Data Strategy

One of the questions we get asked a lot is what to include in a Data Strategy document. It needs to align with your overall business strategy and importantly, be practical. So we’ve compiled a list of the nine fundamental components to make sure you cover, including the vision, resource plan and high-level roadmap. 

Ortecha Alation White Paper: CPG 235 Implementation Fundamentals

CPG 235 is a guideline from the Australian financial industry regulator focusing on data risk management. It is of interest in the focus on data risk compared with the well-known BCBS 239, which looks at risk data. By contrasting the two perspectives, new insights can be gleaned.

How to define your critical data

The concept of a Critical Data Element (CDE) originated when BCBS 239 regulations were brought in to the Financial Service Industry. But there’s still uncertainty about how they should be designated and used. Gareth and Mark take us through best practice in this area.

The role of Data Management in GDPR

The General Data Protection Regulation (GDPR) has had a huge impact on how organisations manage personal data, not only in the EU but across the globe as other jurisdictions follow suit. Mark teams up with Philip from Solidatus to describe best practice. EDM Council membership required to view.

Ortecha Insights: Choosing a Data Catalogue

If you want to use your data effectively, it’s essential to know what it means, where it is, and who owns it. A Data Catalogue can provide a central ‘one-stop-shop’ for the discovery, understanding and enabling of data assets. But how do you choose the best solution for your needs? We share our experience of delivering a successful Data Catalogue procurement process.

Presentations

Accelerating Analytics while complying with Privacy Regulations

In our joint presentation with Alation at the Nashville Analytics Summit in September 2022, Mark discussed how rapid analytic innovation seems to be at odds with the controls and governance needed to comply with data privacy regulations. One is aimed at business growth and the other risk mitigation. How can you strike a balance so you can do both?

All about Ortecha

Learn more about us and the work we do… 

Videos

Have you got your data under control? (2 mins)

Claudia’s got her data under control, and she seems pretty happy about it! How do you feel about yours? 

DAMA webinar: Introducing DCAM (45 mins)

The UK chapter of the Data Management Association (DAMA) offers a wide-ranging events programme. This is a recording of a webinar Pete and Mark did a couple of summers ago, introducing DCAM and our Data Leaders’ Guide. Note that this refers to DCAM version 1.3 (the latest version is 2.2).

Panel discussion: Leveraging the DCAM Framework (30 mins)

In 2021, Pete led a panel discussion at the EDM Council’s EMEA DataVision conference, considering how to leverage the DCAM Framework to establish trusted and actionable data. With thanks to our guests from Lloyds Banking Group, the European Bank of Reconstruction and Development, and Fannie Mae.

Panel discussion: DCAM or CDMC? (30 mins)

In 2022, Mark led a panel discussion at the EDM Council’s Americas DataVision conference, looking at the differences between DCAM and CDMC, and how they complement each other. With thanks to our guests from Morgan Stanley, London Stock Exchange Group and Microsoft Azure.

Solving the Data Management Puzzle: for Data Leaders (55 mins)

We enjoyed presenting the Data & Analytics Management Requirements Model in 2022, developed & contributed by Ortecha using the Solidatus tool, and reviewed & approved by the EDM Council. This one is for Data Leaders and discusses the benefits of using these models. 

Solving the Data Management Puzzle: for Data Practitioners (60 mins)

We were delighted to present the Data & Analytics Management Requirements Model in 2022, developed & contributed by Ortecha using the Solidatus tool, and reviewed & approved by the EDM Council. This one is for Data Practitioners and describes the mechanics of using the models.