What is a proof of concept or implementation of Anjana Data like?

At Anjana Data, our goal is to minimise time-to-market and time-to-value in the proof of concept or implementation of our data governance solution and to be able to demonstrate a real return on investment within a very short time frame.

 We have experienced this first-hand many times throughout our professional careers: acquiring technology with extremely high initial investments, implementation plans with enormous projects, hordes of consultants to configure and test that technology... and then, when it comes time to deliver the Go-Live For the transition to production, after many twists and turns, replanning and budget adjustments, the results are not as expected, no one takes responsibility, and then the entire strategy is rethought.

 That is why, at Anjana Data, we do not believe in that model of mammoth implementations that drag on and seek a Big Bang very difficult to manage and, on the contrary, we advocate pilots and implementation plans based on the same philosophy as agile methodologies, seeking to demonstrate real value in a very short time.

 Furthermore, in order to demonstrate this real value, the implementation of Anjana Data is not limited to the technical tasks necessary to implement the solution; rather, we seek to cover the end-to-end from analysing the need to implementing a first use case in production that allows us to obtain the first measurable results.

So, how do we conduct a proof of concept at Anjana Data? 

First of all, we try to understand as best as possible the client's needs and their main pain points and we began working with him on a proposal for using Anjana Data tailored to his requirements, offering different configuration and usage alternatives for the solution within the capabilities of Anjana Data.

 Next, with the aim of drawing up a detailed work plan with defined activities, milestones and deadlines, we sought to narrow down and define the implementation scenario as precisely as possible, also identifying a series of success metrics that could demonstrate in quantifiable terms what had been achieved and the value obtained.

 Therefore, to achieve this objective, we follow a series of steps that can be grouped into the following blocks: 

1.- We choose a limited use case.

A use case or use case diagram is commonly understood as a description of the activities that someone or something must perform in order to carry out a process.

 In this context, within this first point, we must select a use case where Anjana Data meets the identified needs and its incorporation into the stack technology represents a differential added value. A detailed description of the use case is very important because it will allow us to define the scope of the initial implementation and measure what has been achieved in order to sell it internally.

 Here are some examples of use cases:

• A specific domain of information, for example customer contact details or financial data related to contracts.
• A specific data initiative or project, for example, the creation of a sandbox for advanced analytics or the creation of a product data MDM.
• A regulatory case, for example related to GDPR or RDA.
• A process end-to-end information exploitation, such as the generation of a recurring management report or the generation of the income statement.
• A specific technological environment such as a data lake, a cloud environment, or an analytics area.

No use case is better than another; the selection of the use case will depend entirely on the needs of the organisation, its importance to senior management, the complexity of its implementation, and the ease of achieving the involvement of the stakeholders, among other variables.

2.- We define the technological scenario involved.

Based on the chosen use case, it is important to define the technological scenario involved in this use case, since the more clearly defined it is and the fewer technologies involved, the less complexity we will incorporate into the initial implementation plan.

One of Anjana Data's distinguishing features is its extensive native integration with other technologies to incorporate the data governance solution as the central axis of the data ecosystem. This makes this point particularly delicate, and it is very important not to fall into the trap of trying to cover too many technologies in the initial phase, because there are many aspects of technological integration that can complicate and delay the pilot or implementation plan.

At this point, it is important to identify the following technologies:

• Data storage repositories.
• Data processing systems.
• ETLs and data services.
• Operational and BI tools.
• Identity management systems.
• Permit management systems.

3.- We identify the stakeholders key.

At this point, the people involved must feel empowered to make decisions and see themselves as part of the change process that is about to take place in the organisation, perceiving its value and, in turn, assuming a series of responsibilities regarding data that they may not have had until now.

It is very important to make the stakeholders  that data governance is not about “putting obstacles in the way” or “playing the bad cop”, but rather about equipping the organisation with the necessary capabilities to generate value for the business through better use and processing of data. To do this, it is essential to also provide them with the necessary tools and resources, because without them, their workload will increase and they will not see a quick return.

 That is why during the pilot or implementation plan for Anjana Data, it will be necessary to work on training and change management with the different stakeholders identified. 

4.- We define the metrics for success.

Success metrics will help us to demonstrate in a quantifiable way what has been achieved and the value obtained. These metrics will also depend on the selected use case, but as a general rule we can classify them into the following groups:

• Reuse of data.
• Satisfaction of the stakeholders.
• Cost savings.
• Improved efficiency and productivity.
• Reduction of operational risk.
• Regulatory compliance (if applicable).
• Data monetisation (if applicable).

Anjana Data's pilot or implementation plan

With all this in mind, we outline a project plan with a specific duration (approximately three months), which is agreed upon with the client before commencement. This plan typically includes the following activities:

• Assessment of infrastructure and architecture and technical design proposal.
• Deployment of all services according to the chosen deployment model and configuration of connections with the customer's systems.
• Implementation of the selected use case and support in defining the Anjana Data configuration to meet customer needs (governance model and metamodel).
• Anjana Data configuration as defined.
• Training sessions and change management.
• Support during initial data uploads, functional testing, and use case execution.
• Review of success metrics and drawing of conclusions.

And what do we achieve with this way of working?

Thanks to this approach, we have not only managed to minimise the time to market and the time-to-value in the implementation of our data governance solution, but it also allows us to demonstrate a real return on investment within a very short period of time.

On the other hand, we managed to empower both the organisation and stakeholders so that they can evolve in their implementation of data governance according to their needs and requirements and thus also extend the coverage of Anjana Data to more use cases independently, resulting in a maximum reduction of the dreaded vendor lock-in, from which we try to escape as much as possible.

Furthermore, we always certify Anjana Data implementations, and until certification is complete, the solution's user licences do not become valid. This demonstrates our commitment to our customers and our confidence that Anjana Data meets expectations and fulfils identified needs.