Last Wednesday, June 24th, was held the webinar “MAMDv3.0 como marco de referencia para la creación de un entorno operativo para el gobierno del dato, gestión de calidad de datos y gestión de datos” where we had one of our DQTeam partners as a special guest Ismael Caballero, Professor UCLM & Training Head of DQTeam, spoke about 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.

In the webinar different points were developed that we detail briefly below:

• Data management: good practices in technological infrastructure management to satisfy business requirements.
• Data Governance: good practices in the design of organizational data strategies aligned with business strategies.
• Data quality management: good practices in activities aimed at optimizing 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 organization’s processes related to data management, governance and quality.

MAMDV3.0, Process Reference Model

Components: assess and improve the capacity of the organization’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 a certification).

“Until people consider it normal to resort to data processes like drinking coffee at 11:00, they cannot say they have a data culture”.

If you want to know more about how Anjana Data can help you in data strategy by changing the vision of data governance in your organization, ask for a live demonstration.

You can watch the full video of the “MAMDv3.0 como marco de referencia para la creación de un entorno operativo para el gobierno del dato, gestión de calidad de datos y gestión de datos” 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 June 17, 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 the brief overview of the existing data management & governance maturity models, the description of a methodology to make a brief scan of the maturity in your company, and demonstrate the results of the global data management assessment review.

Here are some of the main points:

Maturity is a measurement of the ability of an organization to undertake continuous improvement in a particular discipline

• Three questions about data management maturity
  • • 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
    • Benchmark the results against the peers in the industry.

• There are two key perspectives on data management and its scope
  • • 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-know 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.
    • 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.
    • Perform maturity assessment and specify follow-up steps.

If you want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

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

On June 10, 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 found out whether Data Governance on a shoe string can be effective and how to go about it. Here are some of the main points:

• To talk about minimal data governance, we must be clear about these concepts:
  • • Shoestring: A small or inadequate budget
    • 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 back?
    • Something that isn’t going to take much effort? 
• Minimal Data Governance has to deliver real value to the organisation or there is no point in doing it. Benefits:
  • • Improve efficiency – reduced costs
    • Accurate reporting – supporting decisions
    • Facilitate compliance
    • Protect reputation with customers and
    • suppliers
    • Enable strategy
    • Provide a single version of the truth
    • Enables safe innovation at pace
• Design Your Framework
• Select Your Deliverables
• Can Minimal Data Governance Be Effective? Just Remember
  • • Very focussed scope 
    • Do it properly 
    • Plan for the future

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

If you want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

You can watch the complete webinar Minimal Data Governance: Is it effective and how to do it? video in 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 impulse, 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 CEO, as presenter of the event spoke with Juan Francisco Riesco, Head of Data at Mutua Madrileña about how the demands of the current environment make being a data-driven company a necessity and 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 & analytics users are:

• 23 times  more likely to outpeform 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 is being 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 people: 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 don’t need everyone in the company to be a data scientist.

Being data-driven means change in: Organization, 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 it translate into the company’s activity?

Business improvements:

• Increased satisfaction and sales
• Process and cost optimization
• New business models
• Increased synergies in partnerships

Operational improvements:

• Better knowledge of what happened
• Anomaly alert
• Predictive suggestions on actions to be taken
• Task automation

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 point of view 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 digitization.

If you want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

You can watch the complete webinar Data-Driven companies: la importancia en el entorno actual y el sector asegurador video in 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 do it?

DAMA – 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 move 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 on the serie “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, CEO of Anjana Data, solved some doubts about Data Management and the importance of Data Governance in the framework of DAMA.

But… What is really Data Management?

To quote DAMA, Data Management is: the development, execution, and monitoring of plans, policies, programs, 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 it has created a framework of excellence and good practices that is a reference worldwide. 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 to 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 and “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 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 it has created a framework of excellence and good practices that is a reference worldwide.
  • • 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
      • Data modelling and design
      • Data storage and operations
    • Security, integration and management of documents and content.
      • Data Security
        Data integration and interoperability
      • 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 starts with the Data Management infrastructure. We will be able to set up a government model as long as we have chosen an infrastructure oriented to it:
  • • • Decentralized organization
      • Organizational Network
      • Centralized organization
      • Hybrid Organization
      • Federated Organization

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 organizational change but also simply because it includes many complex activities that need to be coordinated.
  • A scalable and interactive implementation based on limited use cases maximizes 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 want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

You can watch the complete webinar La importancia del Gobierno del Dato en el framework de DAMA video in our Youtube channel, where you will also find more videos related to Data Governance. You can subscribe to receive notifications of new videos.

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

In this webinar Data Governance 2.0, Data Stewardship & Privacy: Best Practices to operationalize Data Strategy, Peter Kapur talked about re-imagining Data Governance from 2008 Crisis to the opportunity of Data Monetization and Revenue Optimization. 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 after-math of the financial crisis to satisfy Regulators for financial data certification (BCBS 239, Sarbanes–Oxley).
    • Frameworks were creating imbedding Governance components (DAMA, DMBOK). Assessments/Checklists were created (DCAM, DMM). Privacy and Data Protection were added to framework to continue the compliance and Defense path.
    • Data Governance 1.0 framework with Policies and procedure was used across industries even ones not directly impacted by 2008 but based on keeping regulators at bay.
  • Data Governance 1.0 Industry Best Practices – Limited Operationalization Isolated from  Business, Data Innovation & Big Data.
    • Primary focus was not to provide Business value or solve problems but to satisfy regulators. Assumption was that once Policy/Standards/Best Practices were written, everyone would follow them.
    • While Data Governance was steeped in 2008, Data took on strategic value to companies focusing on Data Transformation leveraging Big Data for Operational Efficiency & Revenue Optimization.
    • 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 – Operationalization, Adaption & 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 re-use.
  • Data Stewards are the heroes of Data Governance.
    • Senior Data Stewards must have a Data Leadership position 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 Data Asset Catalog in an organization.

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 organization has authority and control over data assets and how those data assets may be used. It encompasses people, process, and technologies required to manage and protect data assets”. If you want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization, request a demo.

You can watch the complete webinar Data Governance 2.0, Data Stewardship & Privacy: Best Practices to operationalize Data Strategy video in 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): La importancia del Gobierno del dato en el framework de DAMA.

Last Wednesday April 22nd at 18:00, took place our webinar Retos actuales del gobierno del dato para convertirse en data-driven with Mario de Francisco CEO of Anjana Data.

In this first webinar of our series “The DATA-DRIVEN webinar series” we talk about the challenges that an organization 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 organization 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 center of all emerging technologies.
    • Data is classified as an economic asset giving it greater importance for organizations and the world.
    • The vast majority of problems come from people because there is no data culture in organizations. 
• Data governance. From the “what” to the “how” Data governance regulations indicate what is to be controlled and anonymized but do not indicate how, how to keep to it?
  • • Make an assessment and then set the necessary basis to initiate a transformational program of data governance.
    • The “how” has to start with some short, medium and long term objectives.
    • Data governance must be led by Business but aligned with Technology. 
    • The governance model has to be effective and efficient.
    • The incremental and iterative approach based on use cases is important.
• New goals, new challenges. Turning data into a strategic asset.
  • • Data governance is something that has to be extended to all people in an organization, from developers to business users.
    • Trust in the training and talent of employees to be able to extend a data culture in the Organization.
    • Adapt with a new vision our data governance 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 Retos actuales del gobierno del dato para convertirse en data-driven video in 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 want to know more about how Anjana Data can help you in your data strategy by changing the vision of data governance in your organization.

Request a demo.

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

We know that DATA has become a strategic asset for the vast majority of organizations and that terms like 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 divulgating 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 named as “The DATA-DRIVEN webinar series”. It is about an idea that will consist in the broadcasting of a series of webinars of 30 minutes of duration, every two Wednesdays a month, at 18.00 (Spain 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 totally free and open space where we will talk about the challenges that organizations have to face to become Data-Driven. We will share our approach and vision about data governance and management and we will go 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: “Retos actuales del Gobierno del dato para convertirse en data-driven”. In this first webinar in Spanish we want to share some of the challenges that an organization has to face to become data-driven in the current paradigm and give some keys of 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 the knowledge of the attendees regarding 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.