7 reasons why you should consider Anjana Data to successfully implement and operationalise your Data & AI Governance strategy

This article has not used ChatGPT or any other Generative Artificial Intelligence to generate the content but has been produced entirely by a flesh and blood human.

AUTHOR

Let us be clear, most of the strategies of Data & AI Governance The new policies promoted in recent years have failed, are failing or will fail.. And it is not only us who say so, but practically all the experts and the most reputable consultancy firms such as Gartner say so in a multitude of their reports.

In 2024, with the explosion and commoditisation of Generative Artificial Intelligence, the need for effective and efficient Data Governance is once again evident and the vast majority of organisations are beginning (or returning) to focus on launching initiatives to design, implement and operationalise data governance strategies. Data Governance, This time accompanied by initiatives from AI Governance.

This once again opens up a huge opportunity for organisations to transform themselves to finally become Data-driven But there is also the possibility that many of them will fail just as others have in the past, or that even those that have already failed will not have learned from their mistakes and will again make a major blunder.

In this sense, what an organisation may need will vary greatly from one organisation to another and that is why the people in charge of these initiatives and who do not have the necessary knowledge or experience to face the challenge with guarantees, work hard to read articles on the internet, train themselves in different subjects, ask experts, talk to consultants and/or manufacturers, ...

A Data Governance Programme has to be tailor-made for each individual organisation.

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Different approaches to the challenge

In one way or another, these organisations usually end up contracting a consultancy project to a company they trust or they directly buy a technological tool, thinking that this will solve the problem.

From our knowledge of the market, what we see is that the vast majority of proposals for such organisations offer one of the following approaches:

1. Basic «Buy» technology approach: It usually consists of the deployment of a complete ecosystem of one of the major Clouds together with a discourse that claims to cover everything necessary with guarantees at an affordable cost (something that common sense would suggest is more than questionable). O platforms all-in-one which rarely give good results and are usually tremendously expensive and complex. In our humble opinion, we consider this strategy to be wrong because it only seeks to purchase technology and also requires high investments (although at first it may seem otherwise, especially given the aggressive discounts that some manufacturers offer for the first year).
2. Advanced «Buy» technological approach: It includes the implementation of benchmarks comprehensive studies in which the following are analysed different market tools from different perspectives, which then lead to the elaboration of a shortlist of finalists with which they intend to carry out one or more PoCs (often without really knowing what they want to test or what the analysed tools are going to be used for). Apart from the fact that we have seen few exercises of this type that are really well focused with a purpose other than «buying technology to solve a problem". automagically In our humble opinion, it is an exercise that does not add any value to the vast majority of organisations because they are not mature enough to be worth the time and effort required.
3. Build« technological approach: It consists of committing to the realisation of developments in software made-to-measure The problem with this approach is that it only serves to justify expenditure and to deliver something that will partially meet the identified needs. The problem with this approach is that it only serves to fulfil short-term requirements and has a very limited ROI. In addition, this approach does not accompany the organisation as it grows in maturity level, so at some point they will be forced to change their strategy as they will not be able to support the investment necessary to maintain and evolve a custom developed software that adapts to their changing needs and a maturity level that grows over time.
4. Traditional consultancy approach: It is the most typical and widespread and basically involves the realisation of a project of «PPT strategic consulting» which includes excessive analysis work for the subsequent preparation of a large number of «paper» deliverables that provide little or no value to the vast majority of organisations that want to have something tangible in a short time (less than 6 months) with which they can get started and from there grow and scale.

Our vision is that the formula has to be different from previous approaches in the vast majority of cases and that is why we are committed to innovative, differentiated and disruptive approaches and we ally ourselves with those who share our values and our philosophy and who also like to be very practical and pragmatic to be able to bring value to their clients without grandiloquent speeches and with much more reality than PPT, but being clear that technology is not an end but a means to face a business challenge.

The reasons to go for a different approach driven by #genAnjana

If you agree with us so far, then we speak the same language, you will understand perfectly what follows and you will ask us how we can help you.

So, here are the 7 reasons why you should consider Anjana Data to successfully implement and operationalise your Data & AI Governance:

1️⃣ We are recognised experts in Data Management, We have many years of REAL experience among our professionals and we don't sell Smoke and Black Magic. Any tools and/or words you've seen out there that contain Data o AI I'm sure we've read and researched about it and even rolled up our sleeves and got down in the mud in real situations, so we can help you demystify false beliefs, unmask the sell-outs, separate the wheat from the chaff and turn your vision into something down-to-earth that has a real impact on your life. tangible business impact.

2️⃣ We are a Product Company and Software Manufacturer, We don't offer professional services or consultancy beyond what is related to our own technology that we design, develop, maintain, evolve and commercialise ourselves, and we don't get involved where we don't contribute something really differential, so we know well what we do. We sell technology but with a purpose, we hate the Vendor Lock-In, We include a lot of documentation and training, we have a Value Proposition business-oriented, disruptive and differential and a Clear pricing model without small print. And because we are a very niche company, in order to reach where we can't reach alone, we have built a Ecosystem and a Community working hand in hand with our partners, we are unique in partners to offer the best possible service to our customers.

3️⃣ Our value proposition, our team, our technology, our positioning and our business model are endorsed by independent experts such as Gartner, the leading Cloud Service Providers (AWS, Google and Microsoft), several of the most cutting-edge and market-leading Software Manufacturers, top-level Consultancies and Integrators and different Associations, Organisations and Institutions in the world of Data and AI. In addition, we are Innovative SME and company GovTech and we have important certifications such as the National Security Scheme.

4️⃣ We know the market inside out and are aligned with the latest trends. (#DataSpace, #DataLakeHouse, #DataFabric, #DataMesh, #DataMarketplace, #AdaptiveDataGovernance, #DataSharingAgreements, #DataContracts, #DataOps, #AIGovernance, #DataEthics, #DataMonetization, ...) and the main frameworks (#DAMA, #UNE, #Gaia-X, #IDSA, ...), standards and regulations (#GDPR, #DataProtectionLaws, #DataAct, #DataGovernanceAct, #AIAct, ...) at a global level to which we also add our philosophy and vision based on our experience. We are not trying to reinvent the wheel, but rather we are trying to apply common sense and we choose to propose solutions that we have seen that work for specific problems, trying to avoid things that do not work, because we have experienced it in our own flesh.

5️⃣ We have been pioneers in the market for a long time and are always at the forefront. in our field of expertise but we are very practical and pragmatic, This gives us a long-term vision while focusing on the long-term goals of the Quick Wins that everyone wants in the short term. We started 2019 with a jaw-droppingly innovative and disruptive discourse that even the biggest players have now embraced almost word for word but that few have yet managed to truly materialise.

6️⃣ We are empathetic, honest, sincere, approachable, agile and flexible. but also tremendously professional and disciplined. Accompanying our clients in achieving their goals is what drives us and we always give a little bit more when it is needed but to be effective and efficient we need to maintain an methodology that we have proven to work, Our values define what we do and what we do not do, based on relationships of trust and avoiding the more traditional, rigid and heavy bureaucracy. Our values define what we do and the #genAnjana is something that if you catch it, you can go a long way.

7️⃣ Our clients and partners, All of them are leading organisations in the field of Data Management, both in the public and private sectors, and they speak for us. They are the most important and the real protagonists of all this, so we always try to get them to talk to each other, to share their concerns, their ideas, their experiences, their mistakes, their learning and their good practices, and thanks to this we can also grow together to improve our formula. We count on numerous real-life success stories that demonstrate that what we preach can be achieved and that the Proactive and Preventive Data Governance is not a utopia but something possible and achievable for any organisation regardless of its level of maturity.

Speaking of real use cases, here are a few examples

If you've made it this far and like what you're reading, it means that you share our vision, and that of our clients and our customers. partners. HOORAY!

At this point you are ready for us to tell you about some of the different use cases that you can implement with Anjana Data Platform.

As you may already know or have guessed from reading this article, organisations around the world, of different industries, sizes and maturity levels, rely on Anjana Data to implement a wide variety of Data Governance & AI use cases aligned with their data strategies.

Following our philosophy of adding value to the business, we identify among our customers different use cases which have been successfully solved thanks to the incorporation of the Anjana Data Platform in its stack technology, considering technological architectures and Data & AI ecosystems of very different natures.

In this sense, it is also important to identify the global requirements of the organisation in order to be able to provide the most appropriate solution approach to meet its business objectives, which may consider multiple technological architectures incorporating different pieces of different vendors which are natively integrated in order to build a fully governed Data & AI ecosystem.

The following is a comprehensive list of different initiatives that have been successfully implemented by our clients:

BUSINESS OBJECTIVE / USE CASE	SOLUTION APPROACH WITH ANJANA DATA PLATFORM
Foster a Data Culture aimed at eliminating silos and managing information knowledge in a cross-cutting and transparent way to promote the re-use of Information Assets.	Creating a one-stop shop for access to knowledge about the organisation's Information Assets through a Data Portal with a Business Glossary and a Data Catalogue containing all the information needed for any stakeholder, in an understandable language adapted to your profile
Improve the agility and effectiveness of Data and AI-driven decision making by enhancing data quality and reducing the associated risks inherent in the use of data.	Implementing and integrating a flexible Data Governance and AI operational framework that enables the organisation to bring Data Assets closer to business roles by facilitating the application of data governance policies and procedures. stewardship for data quality, security, privacy and ethics
Promote the democratisation and self-service of Information Assets between business areas for different use cases, facilitating the exchange of information in a federated ecosystem.	Building a Marketplace Information that will enable different stakeholders understand the context of Information Assets and share information effectively and efficiently without the need for expertise or technical knowledge, in an environment governed by Data Sharing Agreements and Data Contracts.
Create Data/Information/IA Products that can be monetised and generate new revenue streams through the creation of new business lines, products and/or services.	Adopting an architecture Data Mesh domain-based with advanced capabilities to aggregate, manage and publish different Data/Information/IA Assets in various formats and supported by different technologies, making them available for multiple, diverse use cases
Leverage state-of-the-art Hybrid Data and AI Platforms and Architectures to reduce risk, operational and IT costs associated with Data Management and AI	Implementing a flexible operational model based on the principle of governance by design that integrates existing demand management processes to avoid bureaucracy and bridge the gap between Business and IT, making operational models of Data&AIOps with automation of technical processes within the governance, integration, storage and consumption layers of Data and AI. This model, driven by what is known as the Active Metadata, is the basis for the modern architectures of Data Fabric and Data Spaces
Comply with existing regulations related to Data and AI in a simple way, facilitating the processes of stewardship and the submission of evidence to the relevant Governing and Regulatory Bodies.	Creating a Metadata Lake taxonomy-driven as a single source of truth to meet regulatory and/or normative requirements by standardising metadata management, centralising observability, integrating audits, ensuring traceability and controlling the associated risks
Increasing the productivity of the different stakeholders of Data and Information Assets by reducing the time spent on manual tasks related to Data and IA management and governance.	Creating a federated collaborative environment that facilitates interaction between users while empowering them, and incorporating advanced process automation and recommendation functionalities.

If you identify one or more of these use cases aligned with your strategy, do not hesitate to write to us, we will be happy to help you.