When the number of data initiatives increases across an organisation and the need for executive agreement arises, it is time to define a data management framework and operating models to govern the flow and usage of data throughout an organisation.

We offer guidance and benchmark on data governance, including the definition of operating models (centralised, decentralised, federated), the creation of governance entities (chief data officers), the definition of roles and responsibilities across the organisation (data owners, stewards, custodians, architects) as well as the selection and implementation of unified data governance technology.

Can you see the overall picture of your organisation’s data? Do you understand what types of data are flowing through your systems? Data governance must be delivered on a foundation of robust data reporting models that can be trusted and visualised to demonstrate best data practice.

We offer data architecture services for data reporting and flow visualisation. We support organisations in implementing the right mechanisms to maintain coherent and robust architecture, and the selection of data engineering technology.

Master Data Management typically starts with files systems, ERP and CRM tools, or e-commerce platforms. But when it comes to enterprise-wide master data, many organisations need support to define, maintain and protect their master data.

Our team helps confiure master data operating models and data management practices, and defining match and merge and de-duplication rules that are critical for creating a Single Source of Truth (SSoT). We support the selection of data integration and advanced analytics technology.

In most organisations, knowledge of data assets and their location resides in the minds of individuals. Creating a searchable index and catalogue of all information assets makes information instantly accessible throughout an organisation.

We offer an robust methodology for planning, implementing and maintaining data processing and search engine frameworks from the identification of business cases to index architecture and workflows. We also support selection and implementation of data processing and search technologies.

Metadata are sets of data that describe and enhance other data to improve search, discovery and analysis functions. Metadata management involves establishing policies and processes that ensure information can be effectively generated, integrated, accessed, shared, linked, analysed and maintained across all business functions.

We help you design metadata structure for integration and interoperability and provide guidance for the maintenance of data lineage and the selection and implementation of graph analytics and graph data management technology.

Do you trust your data? What is the level of confidence in your reporting? Data quality is critical for any organisation that intends to make data-driven decisions. While data engineers need the right tools to monitor data throughout its life-cycle, it is data users who should define the rules and monitor quality to inform decisions.

Our team supports organisations to define data quality frameworks and processes. Striving for efficiency and avoiding burdensome over-engineering. We offer and end-to-end service for configuring data quality rule definitions, along with dashboarding, technology selection and implementation.

Governments and regulatory authorities around the world are issuing demanding data privacy and protection laws to protect peoples’ rights and control over their personal information. This challenges organisations in a variety of ways including, data collection, storage, retention, access, deletion and overall security.

Our data team collaborates with our compliance experts in order to provide guidance on data privacy and protection and ensure our clients implement data protection frameworks to enforce regulation by design in compliance with GDPR and other regulations.

Our support the acquisition and production of the highest-quality data and then consistently organise, move and use this data throughout the enterprise, to help clients meet these challenges and effectively manage data on a global scale. We scrub, verify and continually update feeds as events and entities evolve.

Collecting, combining and transforming raw data from multiple sources and delivering it to metadata stores is vital for a data-drievn organisation. Automating data integration processes to generate trusted metadata requires specilialst tools and skills. We offer which presents a significant challenge for most IT functions.

Our team develop data integration software programs and data integration platforms that facilitate an automated data integration process for connecting and routing data from source to target systems.

Organisations are continuously increasing of the volume and range of data they collect which in turn increases the pressure on IT capability. Modern Data Infrastructure provides a platform for integrated data storage and search, and allows you to collect, analyse, govern and reliably deliver information to users.

Our team advises organisations on migrating their data to affordable and scalable cloud storage, including the identification of use cases, the definition of data storage architecture and governance, as well as the selection and implementation of Cloud 2.0 technology.

The volume and complexity of data involved in some client engagements can over-burden in-house teams and data storage capacities, these include data breach analytics and incident response, e-discovery processes and due diligence exercises.

For these kinds of engagements and to support compliance with regulations, we offer a Digital Notary repository service to store information for the duration of a project or complaince period to preserve documents, plain text, electronic records, transaction data and activity logs.

Advanced Analytics is the automated or semi-automated examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations. Advanced analytic techniques include those such as data/text mining, machine learning, pattern matching, forecasting, visualisation, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, natural language processing, complex event processing and neural networks.

Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively. The goal of data management is to help people, organisations, and connected things optimise the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximise the benefit to the organisation. A robust data management strategy is becoming more important than ever as organisations increasingly rely on data assets to create value.

The ETHEL data management framework is a model of the people, processes and policies that is implemented to govern and manage data in compliance with regulations and security controls.

Advanced Analytica configures data management frameworks to ensure our clients have the relevant elements in place to process data and deliver high quality information on a basis of data privacy and protection by design and by default.

Data defense is about minimising downside risk. Activities include ensuring compliance with regulations (such as rules governing data privacy and the integrity of financial reports), using analytics to detect and limit fraud, and building systems to prevent theft. Defensive efforts also ensure the integrity of data flowing through a company’s internal systems by identifying, standardising, and governing authoritative data sources, such as fundamental customer and supplier information or sales data, in a “single source of truth.” - SSoT.

Data offense focuses on supporting business objectives such as increasing revenue, profitability, and customer satisfaction. It typically includes activities that generate customer insights (data analysis and modeling, for example) or integrate disparate customer and market data to support managerial decision making with, for example, interactive dashboards.

A company’s data architecture describes how data is collected, stored, transformed, distributed, and consumed. It includes the rules governing structured formats, such as databases and file systems, and the systems for connecting data with the business processes that consume it.

Information architecture governs the processes and rules that convert data into useful information. For example, data architecture might feed raw daily advertising and sales data into information architecture systems, such as marketing dashboards, where it is integrated and analysed to reveal relationships between advertising spend and sales by channel and region.

The SSOT is a logical, often virtual and cloud-based repository that contains one authoritative copy of all crucial data, such as customer, supplier, and product details. It must have robust data provenance and governance controls to ensure that the data can be relied on in defensive and offensive activities, and it must use a common language—not one that is specific to a particular business unit or function. Thus, for example, revenue is reported, customers are defined, and products are classified in a single, unchanging, agreed-upon way within the SSOT.

An SSOT is the source from which multiple versions of the truth are developed. MVOTs result from the business-specific transformation of data into information—data imbued with “relevance and purpose.” Thus, as various groups within units or functions transform, label, and report data, they create distinct, controlled versions of the truth that, when queried, yield consistent, customized responses according to the groups’ predetermined requirements.

The “plumbing” aspects of data management may not be as sexy as the predictive models and colorful dashboards they produce, but they’re vital to high performance. As such, they’re not just the concern of the CIO and the CDO; ensuring smart data management is the responsibility of all C-suite executives, starting with the CEO.

By combining design thinking, data science, legal expertise and technology, we reimagine the delivery of legal services for multi-national and mid-market clients by integrating unstructured and structured data from multiple sources. We work closely with a worldwide network of the very best lawyers, and AI and technology consultants.

Our objective is to maximise cost and administrative efficiencies through compliance and legal process automation. Throughout the process, equal attention is given to planning and compliance automation.

Customs Compliance and Trade Compliance Consultants specialising in the creation of data-driven customs and global trade solutions and strategies for multi-nationals and mid-market clients, encompassing inter alia customs, freight management and global trade management systems. We work closely with a worldwide network of the very best customs and international trade consultants and lawyers.

Our objective is to maximise cost and administrative efficiencies whilst ensuring compliance with all relevant international trade rules and regulations. Throughout the process, equal attention is given to planning as well as compliance automation.

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