BI & Analytics

Metonomy / BI & Analytics
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GenAI’s Real Opportunity: Empowering Data Teams, Not Replacing Them

There’s no doubt that Generative AI is changing the way people interact with information. But in the race to adopt AI, many organisations are missing a more pressing opportunity. It’s not just about what AI can do for the business; it’s about how it can transform the experience and impact of the data professionals who drive it.

In data and analytics, GenAI should not be seen as a magic fix. It should be treated as a productivity partner, one that helps data teams manage complexity, reduce repetitive tasks and accelerate project delivery without sacrificing quality. The real value lies in empowering analysts, engineers and consultants to spend more time shaping strategy and less time wrangling technical debt.

The Hidden Cost of Manual Metadata Management

Metadata underpins every business insight, yet it is often the most neglected part of the data estate. Analysts spend hours tracking lineage, mapping definitions or translating what a KPI means across departments. GenAI can’t replace that effort unless it’s built on structured, consistent metadata. However, it can assist those managing it.

Instead of expecting GenAI to generate perfect outputs on Day One, organisations should focus on how it can support humans behind the scenes. Think of the automation of metadata audits. Real-time anomaly detection across assets. Simplified language translation between technical documentation and business requirements. 

These are the real pain points data teams face every day, and they are ripe for automation.

From Enablement to Acceleration

At Metonomy, we’re not building AI that promises to do your job. We’re building automation that removes the roadblocks slowing down data teams. 

That means:

  • Helping consultants scope transformation projects more quickly
  • Supporting analysts with accurate metadata insight
  • Giving teams confidence that their outputs align with consistent business definitions

The result isn’t just faster delivery. It’s delivery with fewer surprises, fewer rewrites and more stakeholder trust. When your people can move at speed without cutting corners, transformation accelerates naturally.

A Smarter Strategy for GenAI in Analytics

The question isn’t whether to adopt GenAI. The question is how to deploy it in ways that protect your data integrity and increase human effectiveness. 

That starts with governance. With structured metadata. With systems that learn from your people instead of trying to replace them.

If your organisation is exploring GenAI, focus on how it can enable, not replace, the specialists who already understand your data. Use automation to clear the noise, allowing them to focus on delivering insights that matter.

Redesign the Analyst Experience

We deliver automation that helps data professionals take control of metadata, accelerate their workflows and reduce risk. We turn complexity into structure, and structure into action. 

If you're ready to rethink how your teams work with data, start the conversation with us today.

BI & Analytics - 09/23/2025
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Enterprise Analytics Governance: Why Metadata Assets Matter for Business Success

Analytics only deliver value when everyone understands what they are working with. But as organisations scale their data estate, they often lose control over the meaning behind their numbers. That’s when metadata can either become critical to your success or the very thing that sabotages it.

What We Mean by Analytics Assets and Why They Matter

When we talk about analytics assets, we refer to the building blocks that make data useful: the definitions, rules and logic that shape how business terms are understood and applied across systems. These assets provide the clarity needed for reliable insight, the lineage required for trust and the structure that supports consistency.

Without these foundations in place, executives waste time reconciling conflicting reports and information. Analysts burn hours fixing inconsistencies while teams waste time starting to build workarounds. Trust slowly breaks down and the entire analytics function becomes less effective.

At Metonomy, we see metadata as the nervous system of the data estate. When it’s aligned, automated and governed, it powers faster delivery, more transparent reporting and better decisions. When it’s not, it quietly introduces chaos at every level.

Where Organisations See the Greatest Value

The impact of strong analytics governance becomes visible early. We’ve seen organisations rapidly increase trust in reporting by activating domain ownership and clarifying business terms. Decision-making speeds up significantly when everyone uses the same definitions for revenue, churn or margin.

Standardising metadata doesn’t just help internally. It makes data self-service possible without compromising accuracy. It reduces the need for technical intervention. It increases adoption across the board. Teams don’t just consume reports; they rely on them.

Willem Koenders (Global Leader in Data Strategy at ZS Associates) describes this as laying the operational foundation. Once that’s done, businesses can move towards innovation and strategic impact. Better-governed analytics lead to shorter decision cycles, better outcomes and less rework.

What Drives the Need for Governance

What’s pushing this conversation and why are organisations suddenly prioritising governance?

One reason is fatigue. Businesses are tired of BI rework, failed transformations and tools that promise clarity but deliver complexity. They’re tired of building reports that no one trusts and dashboards that go unused. They’re tired of asking, “Why don’t the numbers match?”

Ramesh Kulkarni (Founder & CEO, InfoKalash) puts it well. Metadata is not just documentation; it’s cognitive infrastructure. When business and technical teams align their mental models through shared metadata, progress accelerates, confidence returns and shadow systems disappear.

Governance That Delivers Real Business Impact

When organisations take governance seriously, they stop firefighting. They know who owns what, they can trace the impact of changes and they spend less time managing problems and more time delivering value.

Success doesn’t come from controlling everything. It comes from ensuring that the things that matter are known, trusted and consistent. And that starts with aligning metadata, embedding standards and enabling the teams that use the data every day.

How Metonomy Supports This Shift

Our platform automates the discovery and alignment of metadata, flags inconsistencies before they escalate and builds governance into the analytics workflow. We give consulting and data teams the tools to deliver with confidence.

By clarifying definitions and reducing manual effort, we help you avoid the downstream problems that derail so many transformation projects. Whether you’re working with partners or internal stakeholders, we make metadata a strength, not a source of risk.

Take Control of Your Analytics Foundation

If your data environment is growing more complex and the pressure to deliver fast, trusted insight is rising, this is the moment to rethink how your organisation governs and uses metadata.

Start a conversation with us or book a walkthrough of Metoscope to see how enterprise analytics governance can become your strongest asset.

BI & Analytics - 09/23/2025
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Are Information Silos Holding You Back?

The Hidden Cost of BI Heritage

Since the early 2000s, businesses have been racing to meet growing demands for data and decision-making tools. However, in the rush to deliver more data, businesses lost control over how it’s used and trusted.

Fragmented BI platforms, disconnected reporting tools and bespoke departmental builds left behind a digital trail of clutter. Along with it came an explosion of metadata. That might sound like a technical footnote, but it’s not. 

The result has been:

  • Conflicting KPIs across teams
  • Growing administrative overhead
  • Frustrated end users losing faith in the data
  • Spiralling IT costs to try to hold it all together

The business impact? 

Delayed decisions, rising costs and a growing disconnect between strategy and execution.

Silos Aren’t Just Systems. They’re Symptoms.

Those isolated pockets of information, hoarded in spreadsheets, buried in outdated BI platforms, or stranded in legacy databases, don’t just slow you down. They block alignment, erode trust and undermine confident decision-making.

This happens not just because of bad architecture but human behaviour, such as:

  • Teams protecting their data
  • Departments optimising for local goals
  • IT serving as a bottle-neck
  • Leadership shifting focus without decommissioning legacy platforms or reconciling outdated data

When Marketing can’t access Sales data, when Operations uses different numbers than Finance or when decisions rely on partial truths, silos quietly erode trust and competitiveness.

As Colin Hendrie (Chief Data Architect at Temenos) puts it, metadata may be “unsexy” but it’s essential. Without shared standards, clear ownership and strong governance, you may end up building dashboards on a crumbling foundation. His warning is clear: if you don’t fix metadata governance, self-service BI becomes self-sabotage.

A New Kind of Automation Is Emerging

We’re now in the fourth generation of automation software.

  • First came data processing
  • Then operational systems
  • Then information management
  • Now it's enterprise analytics governance

This new wave doesn’t just tell you what’s going on. It helps you change it.

It unites organisational, operational and informational silos, streamlines your BI landscape and brings governance, consistency and trust back to the centre of your data strategy.

From Fragmentation to Flow

You don’t need to start from scratch. You need a more innovative approach:

  • Governance:  Build an analytical asset register with consistent, agreed-upon KPIs
  • Architecture: Rationalise BI platforms and cut legacy technical debt
  • Culture: Balance central oversight with local ownership
  • Technology: Automate alignment, not just analysis

This is precisely what leaders like Sofia Kosenko at T-Mobile Spain are delivering through their “Fair Data” strategy. By focusing on findability, accessibility, interoperability and reusability, they’re tackling the metadata sprawl head-on. Their work harmonises definitions, introduces shared glossaries and embeds governance directly into analytics delivery. It shows what happens when strategy and structure finally align.

The businesses that thrive in the next five to ten years won’t be the ones with the most dashboards. They’ll be the ones whose data works together.

Ask Yourself

  • How much is fragmented data costing my business?
  • Do my teams work from the same version of the truth?
  • What’s our current Time-to-Value for business decisions?
  • Have we explored automation as a way to accelerate Cloud adoption, not just improve reporting?

Let’s Talk

Metonomy works with consulting partners and enterprise clients ready to leave BI legacy behind and build something more connected, more trusted and more useful.

Have you tackled your data silos? Or are you still fighting the friction?

We’d love to hear about what you’re seeing.

Further Reading

BI & Analytics - 09/23/2025
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Data & analytics governance

Meeting the challenge?

Today, more than ever, organisations are seeking to harness their information assets as effectively as they can.  Many are introducing automation to improve efficiencies, cloud computing to reduce costs and AI/machine learning to deliver a further range of benefits.  Often the transformation needed by mature organisations with complex IT architectures requires a commitment to complex, multi-year change programmes.

Not addressing the constraints of aging, legacy systems leaves companies vulnerable to new, disruptive entrants that are not hampered by the baggage of the past.  Hence, the strategic, enterprise-wide initiatives being undertaken by organisations of all hues to modernise and become “data driven”.

The creation of executive roles such as Chief Data Officers (CDOs) and Chief Data and Analytics Officers (CDAOs) alongside the wide-spread adoption of data governance initiatives marks the growing importance of controlling data to support corporate strategy.  A focus has been on improving the quality and value of data assets.  Rightly so, as they are the foundation of information that flows and is used throughout organisations.  But what is happening downstream of these on-prem or cloud data stores, lakes or lake houses?...

What control is being applied to Analytics assets?  How are responsible C-suite executives equipped to control and curate the applications that source governed data and produce much of the information used for decision-making?

Most companies that have undertaken some form of digital transformation will continue to use multiple, disparate BI and analytics applications.  This presents a range of challenges that left unaddressed will result in continued issues and the potential benefits from improvements to data assets not being fully realised.  Some of the challenges I’m aware of by team are:

For analysts, developers and support teams:

  • How can we identify inconsistencies and address proactively?
  • How can we analyse issues, react and resolve quickly with reduced effort?
  • How can we simplify and optimise the portfolio of BI & analytics applications?
  • How can we reduce repetitive manual tasks and focus on analysis?

For management:

  • How can we mitigate the risk of mis-reporting?
  • How can we optimise our BI & Analytics resources?
  • How can we deliver change programmes efficiently and with reduced risk?
  • How can we maximise the value of our data and analytics assets?

For consumers of analytic output:

  • What degree of confidence to attach to metrics?
  • Where to find the appropriate information across so many apps?
  • How is information produced and in what context should it be used?

What challenges do you experience in producing or using BI and analytics?  How do you tackle them now and what, if anything, are you hoping for by way of improvement?

Green shoots are emerging in the form of governance practices and new software solutions to help address some of the above.  Metonomy, for one, enables organisations to increase the value of their analytics assets through metadata automation software.  It is now possible, using such solutions, to extend enhanced governance and control to the “last mile” of an enterprise information flow.

We will be sharing more insights and guidance in future posts, so if you are wanting to find out more about governance and how to improve trust in your data, then stay tuned.  Find out more about the art of the possible, today, at: www.metonomy.io.

BI & Analytics - 09/16/2024
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Come dine with me

Controlling and optimising Business Intelligence applications can be a dry topic even for some of us who work in the domain of BI & Analytics.  This shouldn’t limit consideration of the problem area as there can be significant challenges for organisations with associated costs if the challenges are not addressed.  When we think of various analogies that could be used by way of illustration one scenario to consider involves an imaginary restaurant, “Chez Metrique”, from inception to maturity.

OK, following the commitment to invest in Chez Metrique and a period of concentrated effort by the team to design, develop & prepare, the restaurant launch has gone well; customer reviews are positive and bookings are encouraging.  Looking beyond the bright, busy dining room into the kitchen the stations are pristine and organised and processes well-defined.  The staff are appropriately skilled, have a clear understanding of their roles and communicate effectively with each other.  The output is of high quality, delivered promptly by front-of-house and well received by appreciative diners.

So far so good. Chez Metrique is buzzing.

Of course, from this point in time there are many possible outcomes.  For this scenario, let’s take the common path and peer through the restaurant windows 5 years hence.

Unfortunately, it’s not an encouraging sight.  Only a few people are dining – and with a long spoon.  The once-bright and appealing décor has faded and the buzz has gone.  Pan through to the kitchen and there’s a picture of disorganised endeavour.  The remaining cooks, although doing their best, are working without method or direction and producing meals that should carry a health warning.  Regulators (Environmental Health), if aware, would close the place down in a heart-beat. The once-promising enterprise has turned sour through a managerial inability to adapt to shifting demands and sustained under investment.  Chez Metrique is done.

What a waste of potential, resources, effort & time.

There’s a good chance that another restaurant / café will start up on the same site within a few short months.  Will they repeat the journey of Chez Metrique?

And so to the parallel with Business Intelligence & Analytics programmes.  Often there is an initial directed focus with the aim of supporting a strategic business initiative.  The capability is promoted by positive executive sponsorship and transitioned successfully into business-as-usual (BAU) for on-going support & maintenance.  However, all too often that team is under-resourced and, over time, with the pressure of new initiatives being prioritised the quality levels degrade.  Inconsistencies creep-in to data, metrics, reports & dashboards, it becomes harder for BI consumers to locate, understand and trust the integrity of the information they need. The catalogue of objects expands with increasing duplication and redundancy.  Control slips away and what was a key information asset is now a liability.

Most BI applications start out like this restaurant kitchen.

Many are somewhere in between... could benefit from a deep clean, revised menu and restoration of trust rather than being left unvisited and destined to be shut down.

The application may persist for some time as the effort and cost to regain control, clean-up & optimise is judged to be too great; but it’s in a fugue state.  At some point though, after long-term decline, the zombie app will be replaced with a shiny new set of tools at not inconsiderable expense.  Will the organisation’s approach change to investing in people and resources too?  In many cases, not.

It’s clear that chronic technical debt and poor governance contribute to bad outcomes, be it a promising start-up restaurant or an organisation seeking to use BI & analytics for competitive advantage.  Rinse, repeat & fail.  It’s a path followed by many; but, thankfully, not all.

What are your experiences as a consumer of BI or analytics, developer, analyst or manager? What kind of fayre is being served up in your organisation? I welcome your thoughts.

BI & Analytics - 11/16/2022
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Talking about analytics governance

Some like it hot

I had the pleasure of attending the DGIQ conference in San Diego last month.  It had been some time since I had attended an event in person, I think Big Data London '21 was the most recent prior to this, and I was very much looking forward to meeting some of the Data Governance community in the US and exchanging ideas.  Added to this I'd been accepted to present on a topic close to my heart: "Analytics Governance - adding value in the final mile".

Well, I have to report the conference venue was ideal, the event well organised with wide-ranging, topical content, and the participants - speakers, attendees and exhibitors were fully-engaged. Congratulations to Tony Shaw and his team for providing a great forum to exchange ideas.

The presentation was fun to deliver.  Fair to say I was a little apprehensive that a 5pm slot on the first day of conference would yield a low attendance but was happily proved wrong.  Throughout, the audience asked searching, relevant questions on Analytics Governance and I hope they found our discussion as useful and thought-provoking as I did.

Anyway, that reminds me of one stand-out question I received at the Q&A stage of proceedings.  I'd placed an image of the Forum in Rome on the slide with a few question marks peppered across it.  On inviting further questions a hand shot up and someone asked: "When's the best month to visit Rome?".  Drawing on my limited experience I was able to reply along the lines of "June's fine if you don't mind the heat but I'd recommend you skip the Trevi fountain and Spanish Steps...".  Always up for a left-field question.

Other themes touched on in the session related to the need for end-to-end observability from data source to point of consumption, providing quality assurance for analytics output and how automation can drive efficiencies in transformation and migration programmes.  From holiday advice to thorny problems experienced with analytics in the information supply chain - an eclectic mix.

Anyway, the conference gave me an opportunity to listen to people's views on what's being done well in the data governance domain and also areas where challenges remain.  Transpires that Analytics Governance is an emerging topic of interest and it was great to validate this with folks who seemed to relish challenging hubris and "group think".

So, the trip from London was certainly worth it from my point of view.  I got to meet a range of people: practitioners, vendors, polymaths and specialists; and felt that I was able to take the pulse of what's going on in the data governance space.  This domain, a little like San Diego in early June, is warming-up, trending to hot.

Looking forward to another trip to the beach in 2023!

BI & Analytics / Events - 08/15/2022

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