Last Wednesday, 24th June, the webinar was held. «MAMDv3.0 as a reference framework for creating an operational environment for data governance, data quality management, and data management.» where we had one of our DQTeam partners as a special guest Ismael Caballero, Professor at the University of Castilla-La Mancha (UCLM) and Head of Training at DQTeam, discussed the MAMDv3.0 model.

This model has been developed by a group of experts in government and data management, coordinated by the Alarcos group of the University of Castilla-La Mancha in collaboration with the companies DQTeam and AQCLab. It is composed of a total of 20 processes, and these in turn are grouped into 5 levels of maturity.

During the webinar, various points were discussed, which we will briefly outline below:

• Data management: good practices in technological infrastructure management to satisfy business requirements.
• Data Governance: good practices in the design of organisational data strategies aligned with business strategies.
• Data quality management: good practices in activities aimed at optimising business data quality requirements.

The reference model MAMDv.3 (Alarcos Data Improvement Model 3.0) integrates the processes of data management, data quality management and data governance, in a joint and coordinated way, and allows the evaluation and improvement of the capacity of the organisation's processes related to data management, governance and quality.

MAMDV3.0, Process Reference Model

Components: assess and improve the capacity of the organisation's processes related to management, governance and data quality.

Implementation of the DM, DQM and Data Governance processes

1. Identify the most relevant or necessary processes for your reality according to the level of maturity.
2. Adapt the definition of the processes to the circumstances of your company, ensuring that the results of the processes are met.
3. Adapt the definition of the processes to the degree of capacity (process attributes) that you are willing to assume (for certification).

«Until people consider it normal to resort to data processes like having coffee at 11:00, they cannot claim to have a data culture.

If you would like to learn more about how Anjana Data can assist you with your data strategy by changing the vision of data governance in your organisation, request a live demonstration.

You can watch the full video of the «MAMDv3.0 as a reference framework for creating an operational environment for data governance, data quality management, and data management.» on our YouTube channel, where you will also find more videos related to data governance. You can subscribe to receive notifications of new videos.

On 17 June, the webinar “ASSESSING YOUR DATA MANAGEMENT MATURITY” was held, where Irina Steenbeek, Founder of Data Crossroads, spoke about the data management/governance maturity.

In this webinar of “The DATA-DRIVEN webinar series”We covered a brief overview of existing data management and governance maturity models, described a methodology for conducting a brief scan of maturity in your company, and demonstrated the results of the global data management assessment review.

Here are some of the main points:

Maturity is a measurement of an organisation's ability to undertake continuous improvement in a particular discipline.

• Tres preguntas sobre la madurez de la gestión de datos
  • • Why: Key reasons to perform a data management maturity assessment
    • What: The definitions of maturity and data management/governance
    • How: Challenges with existing models
• There are two key reasons to perform a data management maturity assessment.
  • • Define the steps to improve the performance of data management in your company
    • Compare the results against peers in the industry.

• Existen dos perspectivas clave sobre la gestión de datos y su alcance.
  • • DAMA-DMBOK2 – “broad” sense: from the enterprise point of view on the lifecycle of data circulating in a company.
    • DCAM v2.0 – “narrow” sense: from the viewpoint of tasks to be done by data management professionals.

• There are several challenges with well-known data management and data management/governance maturity models.
  • • Fundamental conceptual differences.
    • Differences in the definitions of DM terminology and the content of DM capabilities/functions.
    • DM maturity models can hardly be mapped.
    • The results of different maturity models can hardly be compared.
    • The metamodels of DM models and DM maturity models are not aligned.
    • DM maturity benchmarking is hardly possible.

• Regardless of the chosen approach, you need to perform a data management maturity assessment.
  • • Specify the metamodel of DM used in your company: definition, scope, and key substituted components.
    • Align and map the DM metamodel with the metamodel of the maturity model.
    • Specify maturity levels and define corresponding indicators (KPIs) to measure the maturity.
    • Carry out a maturity assessment and specify follow-up steps.

If you would like to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organisation, request a demonstration.

You can watch the complete webinar ASSESSING YOUR DATA MANAGEMENT MATURITY video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

On 10 June, the webinar «Minimal Data Governance: is it effective and how to do it?» was held, where Nicola Askham The Data Governance Coach spoke about the implementation of data governance. with little or no investment.

In this webinar of “The DATA-DRIVEN webinar series”We discovered whether data governance on a shoestring budget can be effective and how to go about it. Here are some of the main points:

• To discuss minimal data governance, we must be clear about these concepts:
  • • Shoestring: Unsufficient or inadequate funding
    • Data governance on a shoestring: A minimum approach to proactively managing data quality
    • Minimal Data Governance: A minimum approach to proactively managing data quality
• What does that mean?
  • • Just enough to say we're doing it?
    • Enough to keep the regulator off our backs?
    • Something that won't take much effort? 
• Minimal Data Governance must deliver real value to the organisation, otherwise there is no point in doing it. Benefits:
  • • Mejorar la eficiencia – reducir los costes
    • Accurate reporting – supporting decisions
    • Facilitate compliance
    • Protect your reputation with customers and
    • suppliers
    • Enable strategy
    • Provide a single version of the truth
    • Permit safe innovation at a rapid pace
• Design Your Framework
• Select your deliverables
• Can Minimal Data Governance Be Effective? Just Remember
  • • Very focused scope 
    • Do it properly 
    • Plan for the future

Nicola Askham also shared a Free Data Governance Checklist that provides you with a high-level outline of the activities you need to complete in order to successfully design and implement a Data Governance Framework.

If you would like to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organisation, request a demonstration.

You can watch the complete webinar Minimal Data Governance: Is it effective and how to implement it? video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos. 

The sector of activity and the motivation of the company determine the momentum, scope, and focus of the data-driven transformation.

The Data-driven companies webinar: the importance in the current environment and the insurance sector of the «The DATA-DRIVEN webinar series» was held on Wednesday 3 June where Mario de Francisco, Anjana Data’s Chief Executive Officer, as presenter of the event spoke with Juan Francisco Riesco, Head of Data at Mutua Madrileña, on how the demands of the current environment make being a data-driven company a necessity and how having degrees of freedom beyond regulatory requirements is key to demonstrating that it is a business issue.

Why do we talk so much about data-driven companies?

According to a study by management consulting firm McKinsey & Company, data-driven companies with intensive data and analytics users are:

• 23 times more likely to outperform competitors in acquiring new users.
• 19 times more likely to achieve above-average profitability
• 15 times more likely to deliver better value to their customers.

Data Wrapping

A company's products are «wrapped» in data analytics features and experiences that help and delight customers, with profitable results.

But what does it mean to be a data-driven company?

• Data-driven companies: Data-driven areas + Strategy + Innovation
• Data-driven areas: People & Processes data-driven + Culture
• Data-driven processes: Data + Tools + People data-driven
• Data-driven individuals: Data + Tools + Knowledge + Use

In data-driven companies, we need all people in the company to use data and leverage the data for the performance of their day-to-day tasks. We need to have data scientists with knowledge in statistics, programming, and business, to gain advanced analytical models for the company. We do not need everyone in the company to be a data scientist.

Being data-driven means change in: Organisation, Technology, Processes and Culture.

Regulation: imposition setting the objectives and the regulatory pace
Market: following trends but with limited or diffuse objectives
Business: purpose aligned with company strategy

How does this translate into the company's activity?

Business improvements:

• Increased satisfaction and sales
• Optimisation of processes and costs
• New business models
• Increased synergies in partnerships

Operational improvements:

• A better understanding of what happened
• Anomaly alert
• Predictive suggestions on actions to be taken
• Automatización de tareas

Is it necessary in the current context of insurance companies?

• More data available: Open data and Connectivity
  More accessible capabilities: Advanced analytics and new technologies.
  More complex environments: More competitive market and more demanding customers.

Insurance sector from the perspective of data

Challenges and Opportunities from the point of view of data for the insurance sector regarding the following points:

• Complex business.
• Risks and regulation.
• Technological ecosystems.
• Little digitisation.

If you would like to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organisation, request a demonstration.

You can watch the complete webinar Data-driven companies: their importance in today's environment and the insurance sector video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

>>> Next webinar: Minimal Data Governance – is it effective and how to implement it?

LADY – the International Data Management Association – elected its first board of directors in 1988. The first chapter was founded in 1980 in Los Angeles. From that moment on, it became clear that the most urgent thing in an industry that was starting to take its first steps was to have a unique theoretical framework. A language that all professionals could understand and that would be a reference when dealing with any Data Management project.

In this third webinar in the series «The DATA-DRIVEN webinar series» we had the pleasure of talking with Michele Iurillo, member of the board of directors of DAMA Spain and Founder of Synergo! who, together with Mario de Francisco, Chief Executive Officer of Anjana Data, resolved some queries regarding Data Management and the importance of Data Governance within the framework of DAMA.

But… What is Data Management really?

To quote DAMA, Data Management is: the development, execution, and monitoring of plans, policies, programmes, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their life cycles. From its foundation in 1980 to 2020, many things have changed, there are new technologies, there are even companies that have among their assets almost exclusively data, but DAMA's methodology is still the best foundation for a professional who wants to focus his or her knowledge on information assets. DAMA defines Data Management as a set of 11 knowledge areas and, thanks to the DMBoK 2 reference, has created a framework of excellence and good practices that is a worldwide benchmark. A volume of more than 700 pages that DM professionals use and quote almost like the Bible. The DMBoK 2 has created a framework of excellence and good practice that is referenced worldwide. This methodology identifies Data Management in 11 Areas.

There are many frameworks, but DAMA resists technology and paradigm changes because it is oriented towards a more semantic and philosophical side of DM. If it is true that someone says that there are «poets» missing from Data Management, they surely have DMBok2 on their shelves.

Here are some important points from both presentations:

DAMA: A Framework for Data Management

• It is the data that allows us to move from the dimension of «how» to do things to the dimension of «what» makes sense to do, which is the real turning point of the Digital Transformation.
• Data Governance, what is data governance? «Data Governance is the exercise of decision-making and authority for data-related matters,» definition by the Data Governance Institute.
• If we follow DAMA's approach to Data Management, Data Governance is the central element. There is no Data Management without it.
  • • Data governance prepares us for the digital transformation process.
    • Data governance helps us to make efficient decisions.
    • Data governance enables us to improve processes.
    • It maximises the revenue generation potential of data and leverages the lineage of data.
• The DAMA methodology defines Data Management as a set of 11 knowledge areas and, thanks to the DMBoK2 reference, has created a framework of excellence and good practices that is a worldwide benchmark.
  • • It is not possible to have adequate control of data and transform it into reliable information without addressing the DM in its entirety.
      • Data Governance
      • Data architecture
      • Modellisation et conception des données
      • Data storage and operations
    • Security, integration, and management of documents and content.
      • Data Security
        Integración de datos e interoperabilidad
      • Document and content management
    • DW & BI, Master data, metadata and quality.
      • Reference and master data
      • Data warehousing and Business Intelligence
      • Metadata
      • Data quality
• Data governance begins with the data management infrastructure. We will be able to establish a governance model as long as we have chosen an infrastructure geared towards it:
  • • • Descentralised organisation
      • Organisational Network
      • Centralised organisation
      • Hybrid Organisation
      • Federated Organisation

Data governance in the DAMA framework

According to the DMBoK2:

• • Data governance is defined as the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.
  • The data governance function guides all other data management functions.
    The purpose of data governance is to ensure that data is managed correctly, according to defined policies and best practices.
  • Data Governance vs. Data Management = Oversight vs. Execution
  • Data governance requires planning, not only to represent organisational change but also simply because it involves many complex activities that need to be coordinated.
  • A scalable and interactive implementation based on limited use cases maximises the chances of success and reduces potential frustration in the teams involved.

And something also VERY IMPORTANT: The technology of being an enabler and accelerator for data governance but not solving the basic needs by itself, needs strategy, people and processes.

If you would like to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organisation, request a demonstration.

You can watch the complete webinar The importance of Data Governance in the DAMA framework video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

On 6 May 2020 Mario de Francisco, CEO at Anjana Data presented Peter Kapur, Founder of True North Data. Together delivered the second webinar in the series “The DATA-DRIVEN webinar series”. 

In this webinar Data Governance 2.0, Data Stewardship & Privacy: Best Practices to Operationalise Data Strategy, Peter Kapur discussed re-imagining Data Governance from the 2008 Crisis to the opportunity of Data Monetisation and Revenue Optimisation. Here are some of the main points:

• • Data Governance – Historically, has focused on Compliance and Regulations. 
    • Data Governance 1.0 came to prominence in the aftermath of the financial crisis to satisfy regulators for financial data certification (BCBS 239, Sarbanes–Oxley).
    • Frameworks were created embedding governance components (DAMA, DMBOK). Assessments/checklists were created (DCAM, DMM). Privacy and data protection were added to the framework to continue the compliance and defence path.
    • Data Governance 1.0 framework with policies and procedures was used across industries, even those not directly impacted by 2008, but based on keeping regulators at bay.
  • Data Governance 1.0 Industry Best Practices – Limited Operationalisation Isolated from Business, Data Innovation & Big Data.
    • The primary focus was not to provide business value or solve problems, but to satisfy regulators. The assumption was that once policies, standards, and best practices were written, everyone would follow them.
    • Whilst data governance was steeped in 2008, data took on strategic value for companies focusing on data transformation, leveraging big data for operational efficiency and revenue optimisation.
    • Initially, Data Governance attracted IT Governance professionals to support Regulations, but the profession is now more diverse. There is tremendous opportunity in Data Governance innovation.
  • Data Governance 2.0 – Operationalisation, Adaptation & Enabling Business Innovation.
    • Evolving Data Governance from a perception of “Policy & Compliance” to delivering tangible value and innovation to the business.
    • Part of Data Governance 2.0 is already underway with companies embedding Data Governance with Data Strategy & Analytics.
    • Business sponsors, data producers, and consumers are critical to the creation of a “connected” data strategy that enables strategic reuse.
  • Data Stewards are the key figures in Data Governance.
    • Senior Data Stewards must hold a Data Leadership position in order to build Data Culture.
    • It must be more than metadata and business terms and must be involved in a holistic view of data assets.
    • They must be involved in the maturation of the Data Asset Catalogue within an organisation.

Within these issues, Peter Kapur presented a definition of Data Governance in line with Anjana Data's vision: “Data governance is a system for defining who within an organisation has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets. If you would like to know more about how Anjana Data can assist you in your data strategy by changing the vision of data governance in your organisation, request a demonstration.

You can watch the complete webinar Data Governance 2.0, Data Stewardship & Privacy: Best Practices to Operationalise Data Strategy video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

>>>>> Register for the next webinar (in Spanish): The importance of data governance in the DAMA framework.

Last Wednesday, 22nd April at 6 p.m., our webinar took place. Current challenges for data governance to become data-driven with Mario de Francisco, Chief Executive Officer of Anjana Data.

In this first webinar of our series «The DATA-DRIVEN webinar series» we discuss the challenges that an organisation has to face to become data-driven in the current paradigm. Here are some of the main points:

• What does it mean to be data-driven? A data-driven organisation is one that understands data as a strategic asset and bases its decisions on data analysis and interpretation. 
  • • We start with «stupidity» when making decisions and from the moment data is incorporated into management, we will grow in the scale of value until we achieve a «knowledge» that will allow us to make better decisions. 
    • There is a new paradigm known as the fourth industrial revolution that places data at the centre of all emerging technologies.
    • Data is classified as an economic asset, giving it greater importance for organisations and the world.
    • The vast majority of problems come from people because there is no data culture in organisations. 
• Data governance. From the «what» to the «how» Data governance regulations indicate what is to be controlled and anonymised but do not indicate how, how to comply with them?
  • • Conduct an assessment and then establish the necessary foundation to initiate a transformational data governance programme.
    • The «how» must begin with some short-, medium- and long-term objectives.
    • Data governance must be led by Business but aligned with Technology. 
    • The governance model must be effective and efficient.
    • The incremental and iterative approach based on use cases is important.
• New goals, new challenges. Converting data into a strategic asset.
  • • Data governance is something that must be extended to everyone in an organisation, from developers to business users.
    • Trust in the training and talent of employees to be able to extend a data culture throughout the organisation.
    • Adapt our data governance with a new vision to a current value-added architecture.
    • More traditional market solutions do not bring as much value to the business.

Mario de Francisco, also mentioned Anjana Data's vision of this whole current technological scenario, explaining her focus on the «how» rather than the «what». He mentioned some of the main points of the proposal that the solution offers as added value.

You can watch the complete webinar Current challenges for data governance to become data-driven video on our YouTube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

If you would like to learn more about how Anjana Data can assist you with your data strategy by changing the vision of data governance in your organisation.

Request a demonstration.

• • Next webinar: «Data Governance 2.0, Data Stewardship & Privacy: Best practices to operationalise data strategy«.

We know that DATA has become a strategic asset for the vast majority of organisations and that terms such as data-driven have become fashionable among data managers. Moreover, the current technological scenario offers us all the necessary capabilities to bring DATA closer to the business than ever and generate added value thanks to its appropriate use. However, we still see many unresolved issues and a long road ahead that we want to help you travel.

For this reason, and following our philosophy of disseminating and sharing experiences and best practices for effective and efficient data management, at Anjana Data we have decided to launch a new initiative that we have decided to name as «The DATA-DRIVEN webinar series». It is about an idea that will consist of broadcasting a series of webinars lasting 30 minutes, every other Wednesday of the month, at 6 p.m. (Spanish time). The sessions will be in Spanish or English, depending on the speaker, the topic and the participants, and each one will cover a specific topic.

These webinars will be a completely free and open space where we will discuss the challenges that organisations must face in order to become data-driven. We will share our approach and vision regarding data governance and management, and we will delve deeper into key aspects for the implementation of your data strategy.

All this, in addition, with the collaboration of special guests who will share with us their experience and knowledge on particular topics.

How to attend “The DATA-DRIVEN webinar series”?

«The DATA-DRIVEN webinar series» will be held for the first time with the webinar: «Current challenges facing the data governance team in becoming data-driven”. In this first webinar in Spanish, we want to share some of the challenges that an organisation has to face to become data-driven in the current paradigm and provide some keys on how it can face them with guarantees according to our vision and approach.

This first webinar will mark the beginning of the agenda of «The DATA-DRIVEN webinar series», an initiative with which Anjana Data also seeks to increase attendees' knowledge of data governance, with special emphasis on good practices related to data-driven strategies and the experiences shared by our guests.

Check out the upcoming webinars on our Events page.