EDEco differs  from and is much more complicated than technology/platform-based data ecosystem that many vendors discuss about. DataEco Lab provides technology-independent methods and enablers to help organisations understand scope, context and complexity of EDP or  EDEco as data capability, in particular

• We use an ecosystem approach to complexity management through  modelling, capturing and managing elements, activities/processes and their complex relationships in context of EDEco; 

• We work closely with stakeholders to effectively identify gaps, issues and risks in the current information technology and data practice while your organisation is embrace Big Data applications and considering digital transformation, and assist the organisation to find the best practice and adequate solutions;

• Through using specific scientific and engineering lenses, we help data practitioners and decision makers understand and evaluate new concepts, methodologies and technologies  (such as data mesh and data fabric) in terms of their roles, impact,  and potential benefits, outcomes and risks if they consider to adopt or apply in the specific EDP;

• We assist IT/data executive teams in planning, guiding and organising effective and collaborative activities in data analytics and data engineering, and managing their outputs and outcomes;

• We help organisations systematically and effectively involve all data professionals and stakeholders to participate in capturing, documenting and managing metadata, data-related knowledge and various data models/schemas;

• We provide methods and enablers to help review and assess the existing data governance and management practice; and to support and facilitate materialising and operationalising implementation of data governance throughout the entire EDP or EDEco, rather than only focusing on data alone; 

• We assist organisations to conduct meaningful and goal-oriented surveys on data sources, data applications, data technologies and governance practice as required; and

• We assist organisations in developing and managing organisational data capability, and facilitating organisational learning and knowledge management for EDP.

Expected benefits and outcomes:

• Accessing and using a state-of-the-art methodology for EDPM;

• Knowing and understanding your EDP and EDEco as a whole through using model-driven methods and integrated lenses for highly desired understandability, visibility, observability and assessability;

• Ability to deal with challenging tasks and issues across areas and teams;

• Enhancing progresses and achievements made in different areas by different teams with positive global impact to the whole EDP;

• Ability to effectively fill gaps or holes and mitigate risks in operation of EDP and during the implementation of changes and evolution; and

• Ability to ensure  the returns and outcomes to be achievable for the committed resources and investments  in EDP.

DataEco Lab is a specialist in planning and implementing digital transformation. Based on a conceptual reference model and a maturity reference model for EDP, we help organisations to:

• Understand the knowledge complexity of EDP facing professionals and organisations; 

• Construct a dashboard of concepts, initiatives, operation and management activities, professionals, features  and outcomes of EDEco operation;

• Assess maturity of EDP or EDEco, and identify issues and needs; 

• Analyse and evaluate impact resultant from changes of technologies /tools and governance requirements and practice;

• Analyse and manage operation status and sustainability of EDEco; and

• Understand trends and new directions, make informed decisions, and plan for changes and evolution, such as whether and how to use or adopt new concepts, approaches or strategies (i.e. data fabric and data mesh), and how a digital transformation strategy or plan can be adequately made and effectively executed.

Digital transformation is not just about decisions on the changes of systems and selection of new technologies or platforms. DataEco Lab can help your organisation to make evidence-based and well-informed decisions on changes and evolution of EDP and develop the bespoke digital transformation plan either from traditional ICT  (or enterprise systems)-focussed strategy and practice into a EDP management practice, or to consider and implement major changes to key elements in EDEco (such as cloud migration, replacement of existing technology, and adoption of new technologies or new approaches (i.e. Master Data Management, Data Mesh, data product management or integrated metadata management). The EDP management is an emerging task and the joint responsibility of CIO, CDO and CTO for a modern data-driven organisation. 

Expected benefits and outcomes, in addition to effective EDPM:

• Ability to effectively deal with complexity in different aspects of EDP, in order to conduct meaningful context and operation analysis;

• Enhanced confidence and effectiveness in communications and collaboration across areas and teams as needed; and

• Ability to make informed decisions for changes, evolution and transformation required for EDP or EDEco.

Data architecture and data knowledge management are critical to data-driven organisations, but remain as challenging issues, especially for crossing systems/platforms/tools or the whole EDP. We help organisations:

• Construct a portal for consolidated data architecture of EDP along with enterprise architecture practice;

• Construct EDEco body of knowledge (EDEBoK) through using an integrated solution and practice for processes to capture and manage catalog, metadata, lineage, complex relationships, and EDP operation knowledge;

• Explore and navigate on various elements and their complex relationships and contexts in EDEco through a range of flexible element-based views (EDEco-360) to deliver much improved discoverability and observability in various aspects of data and EDP; and 

• Facilitate setting and planning contexts for data engineering activities, and coordinate and manage them and their outcomes as part of Enterprise Data Engineering.

Expected benefits and outcomes:

• Systematic and effective solutions for data model and architecture management, and the practice towards sustainable organisational learning and knowledge management across EDP; 

• An effective practice to establish a single source of truth for EDP and EDEco;

• Ability to achieve and maintain discoverability and observability to the entire EDP; and

• Improved capability and confidence in dealing with changes (not only data and technology but also workforce) and evolution of EDEco.

Data products can not be effectively created, managed and used in a poorly managed EDP environment or EDEco, for either internal purposes (such as suggested by the data mesh strategy, dashboard-based productisation  or internal 'marketplace'), or external purposes or requirements (such as Open Data, Open Banking, sharing data across organisations or data trading). 

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We introduce and bring the best practice (methodology-based and integrated with EDP management practice ) to your organisations when you are considering and ready for the next level of data practice, that is, data product-based practice for more effective management in data quality and observability, and for seamless data sharing and flowing across boundaries or trading in marketplaces. 

DataEco Lab helps organisations to develop a phased approach to implementing its digital transformation strategy in data democratisation and productisation,  in order to achieve controlled and smooth transitions or shiftings in relevant aspects with clearly defined milestones and outcomes, and enable effective communications and coordination across different areas and teams. 

Expected benefits and outcomes:

• Accessing and using a state-of-the-art strategy and approach to data democratisation and productisation for your purposes, that is, either the internal (such as towards Data Mesh) or the external (for Open Data and data sharing and trading);

• Ability to plan, create, manage and use well-defined data products in clear context of EDEco, in terms of relationships to existing relevant datasets, tools, integration solutions and governance arrangements;

• Ability to ensure the practice of data product development and management not only  fits the current EDP but also is evolvable within its EDEco.