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Tag: Data Strategy

How AI Is Rewriting the Enterprise Data Playbook

Posted on by Luka Jasionyte

Luka Jasionyte, in the marketing team at Snap Analytics, catches up with Tom Bruce, Group Managing Director & Co-founder, to get the lowdown on his journey through data and analytics, and to share insights on what he thinks are the most important trends, AI initiatives and challenges facing enterprise businesses today.  

What inspired you to get into data and analytics, Tom? 

My love for sports statistics and data, along with their transformative impact on sport itself, inspired me. Books like Moneyball showed me how data and analytics can help organisations, making me realise the considerable influence I could have on companies with a relatively small amount of resource. 

What is the most exciting trend right now? 

It’s the obvious answer but clearly AI is already transformational and seeing the applications and more importantly the evolutions that will happen within this space is going to be exciting. With the rate of development and change increasing the impact on productivity, the way we work and the benefits this brings to business makes it a thrilling development to be a part of. We’ve been working on some exciting and transformational AI initiatives with clients, and everyone in this space shares the buzz about the potential and opportunities available now and into the future. 

What are some common data-related challenges that large enterprises typically face? 

I’ve been seeing two big challenges that large enterprises face when it comes to data, and these aren’t exactly new issues, but they’re becoming even more crucial now with the push towards AI-based solutions. 

First off, there’s data quality and governance. It’s all about having the right data, properly managed and owned in a way that’s governed and easily accessible to everyone who needs it. The challenge here is ensuring that the data is accurate, consistent, and reliable. Without good data quality and governance, any AI solution built on top of it is likely to be flawed or ineffective. 

Then there’s data modelling. This is about setting up the right foundations with an optimised and easily understandable data model. It’s key to making the most out of AI solutions. A solid foundation ensures that everything else works smoothly and efficiently, allowing AI to deliver its full potential. If the data model is too rigid or poorly designed, it can limit the effectiveness of AI and make it harder to adapt to new requirements or changes in the business environment. 

So, while these challenges aren’t new, they’re definitely more important now than ever before. 

What are the top client priorities for those looking to drive successful outcomes in data and analytics? 

We’ve often seen that a lot of investment has gone into cloud solutions, but there hasn’t always been control over the costs associated with these investments. Cost optimisation for cloud solutions is something that is increasingly coming up on our clients’ agendas. It’s becoming clear that while the cloud offers immense flexibility and scalability, without proper cost management, it can quickly become a financial burden. Clients are now more focused on finding ways to optimise their cloud spending to ensure they are getting the best value for their investment. 

Similarly, there have been numerous Gen AI exploration projects as organisations are just getting started with AI. We’ve noticed that there often isn’t a suitable business case for these initiatives, and most aren’t taken through to production. It’s crucial to properly identify the value of AI initiatives and ensure that more focus is given to clearly scoped AI projects with tangible business benefits. By doing so, organisations can avoid wasting resources on projects that don’t deliver real value and instead concentrate on initiatives that have a clear and measurable impact on their business.  

The key priorities for clients looking to drive successful outcomes in data and analytics are cost optimisation for cloud solutions and a focused approach to AI initiatives with well-defined business cases. 

Tom, why Snap Analytics? 

We’re experts in delivering the data foundations essential for successful AI projects. Our team is dedicated to ensuring our customers get the best service, reflected in our high retention rates and excellent feedback.  What sets us apart is our focus on our customers. We understand every business is unique, and we tailor our solutions to meet each client’s specific needs. Whether it’s optimising data quality, implementing robust governance frameworks, or developing cutting-edge AI models, we’ve got you covered. 

Our clients know they can rely on us to deliver results. We’ve built a reputation for being the team businesses turn to for new and innovative solutions. We’re constantly pushing the boundaries of what’s possible and are excited to help our clients achieve their goals. We’re here to provide the expertise, support, and innovation you need to thrive in today’s data-driven world. 

Your Enterprise Data Isn’t Aligned and It Shows 

Posted on by Luka Jasionyte

Luka Jasionyte, from the marketing team at Snap Analytics, catches up with Raj Shah, Director of Strategic Accounts, to dive into his journey in data and analytics and explore the key challenges facing enterprise businesses today. Raj shares his insights on making sense of enterprise data, tackling data silos, the importance of strong governance, and how AI and high-quality data engineering are shaping the future. 

What inspired you to get into data and analytics, Raj? 

I was inspired by the opportunity to work across a variety of clients and industries, as data exists in every organisation. The business value that proper analytics can deliver feels almost magical, and although I didn’t enjoy programming, I found SQL surprisingly easy to write and understand.

What is the most exciting trend right now? 

AI, without a doubt. It has really focused everyone’s attention on getting their data right. It’s no longer something organisations can put off while continuing with manual or Excel-based analytics. AI depends on high-quality data, and ‘human-in-the-loop’ AI is the stepping stone for most organisations. Those that fail to embrace it risk being left behind.

What are some common data-related challenges that large enterprises typically face? 

Large enterprises often face several recurring data challenges that impact their ability to deliver reliable analytics. One major issue is the lack of a common data definition or language across the organisation. For example, a term like ‘margin’ can mean different things to different departments, leading to inconsistent reporting and decision-making. Another challenge is the reliance on flat files and manual data processing methods. These approaches are time-consuming, error-prone and make it difficult to scale analytics effectively. Excessive data transformation and manipulation often happens within front-end tools rather than being pushed down to the data warehouse. This creates inefficiencies, performance bottlenecks and governance risks.

What are the top client priorities for those looking to drive successful outcomes in data and analytics? 

For clients aiming to achieve successful outcomes in data and analytics, several priorities stand out. First, making data a true business asset is essential. This involves consolidating information from multiple systems into a clean, unified data warehouse that provides a single source of truth. Second, building data literacy across the organisation is critical. When teams understand and trust the data, they can make informed decisions and fully leverage analytics capabilities. Finally, reducing reliance on manual processes and Excel-based reporting is a key step towards scalability and efficiency. Moving to automated, integrated solutions not only saves time but also improves accuracy and enables advanced analytics. Together, these priorities create the foundation for delivering actionable insights and driving measurable business value.

Raj, why Snap Analytics? 

Clients choose Snap because we combine deep industry expertise with technical excellence. Our consultants have broad experience across the modern data stack, enabling us to design and deliver solutions that meet diverse business needs. We also bring specialised knowledge of complex systems such as SAP, supported by proven frameworks that reliably extract data and integrate it into modern cloud platforms. This ensures accuracy, scalability and speed. Snap focuses on delivering real business value. Every project is driven by outcomes that matter, whether that’s improving decision-making, reducing costs or accelerating innovation. Our approach uses lean teams, automation and reusable frameworks to achieve efficiency, standardisation and strong governance, giving clients confidence that their investment translates into measurable results.

It’s Official: SAP and Snowflake Are Now an Item!  

Posted on by Jan van Ansem

For many large organisations, SAP and Snowflake are core pillars of their data strategy. But getting data to flow smoothly between the two has often been tricky and rarely seamless. So, news of the Snowflake and SAP partnership that was announced earlier this week is definitely going to be well received and welcomed by anyone who has wrestled with the challenges. As SAP experts, we’ve been guiding our clients along this journey and have written a number of blog posts and guides helping them to understand the intricacies and constraints inherent with unifying data sources. 

So, after months of speculation and whispers, we’re buzzing with news of this long-awaited partnership and there’s a real sense of excitement now that we’re starting to see what this collaboration looks like. So, here’s a quick round up of what we know now.

Two New SAP Products: SAP Snowflake & SAP BDC Connect for Snowflake 

Two new SAP products have been announced. Let’s take a look at them.  

  1. SAP Snowflake 

SAP Snowflake is being launched as an SAP Solution Extension, which means it’s officially certified and supported by SAP. With SAP Snowflake customers can finally harmonise SAP and non-SAP data in a unified business fabric. This means we’ll get more zero-copy sharing, enriched modelling and real-time, business-ready data to enable all your data engineering, analytics, and AI/ML workflows with a complete, up to date view of your enterprise data landscape.  

But this partnership isn’t just about shifting data. It’s about making it work smarter. This solution will simplify AI governance and grounds AI in organisational knowledge to build AI agents and intelligent applications that are context rich as well as secure.  

There is currently no information on the technical architecture or how licensing will work, and what limitations might apply, but SAP Snowflake is expected to go to general availability in Q1 2026, so we should get more clarity soon. 

2.   SAP Business Data Cloud Connect for Snowflake (SAP BDC Connect) 

SAP BDC Connect is SAP’s flagship data platform, widely adopted as the go-to data warehouse for SAP-centric environments. But here’s the catch: most enterprises also run a second data warehouse for non-SAP data. Eventually, both sides need to talk to each other, and that’s where things get messy; duplicated effort, higher costs, and frustrated BI teams. 

That’s why seamless integration between BDC and platforms like Databricks and Snowflake has been a long-standing wish for data platform managers. With the existing Databricks connector and now the new Snowflake integration, that wish is finally coming true. 

“SAP BDC Connect – Snowflake is a cloud service enabling bidirectional, zero-copy data sharing with Snowflake AI Data Cloud. Companies already using Snowflake can leverage SAP BDC Connect for Snowflake to integrate their existing instances of Snowflake with SAP Business Data Cloud for seamless, zero-copy access. This integration gives Snowflake users real-time access to semantically rich SAP data products — without duplication.” 

Again, there is no technical deep dive just yet, and licensing details are still under wraps. The product is expected to go live in H1 2026, so we’ll have to be patient a little longer. 

The SAP Snowflake partnership represents a true step-change for enterprise data beyond merely addressing a technical hurdle 

This isn’t just about solving a technical challenge. Yes, there are already solid third-party tools that handle near real-time SAP data integration, and they’ll likely remain competitive in terms of price and performance. But SAP is more than just an application. It’s the backbone of critical business processes across industries, backed by more than fifty years of deep domain expertise. SAP also delivers rich business content from prebuilt data models and BI reports to AI-powered apps, but adoption has been limited, often due to the complexity of the underlying tech. 

Now, with native integrations into Snowflake and Databricks, SAP has a real opportunity to bring that content to a broader audience. Imagine AI-driven insights on supply chain, financial planning, or customer lifetime value (see this article), all powered by SAP data, but surfaced in the platforms that data teams already love. 

If SAP, Snowflake, and Databricks truly align on delivering ready-to-use, AI-enabled data products, it could dramatically simplify how enterprises manage and use their data; potentially cutting integration efforts by 75%. 

The devil is in the detail: licensing restrictions 

SAP has a bit of a reputation for keeping tight control over what customers can do with their SAP data. In contrast, platforms like Snowflake and Databricks are all about openness, designed to support just about any workload you can imagine. 

So, while this new partnership might look like SAP is finally throwing open the doors, it’s worth staying cautious. Even if the data makes it into Snowflake or Databricks, SAP could still impose legal or licensing restrictions that limit what customers can do with it. 

Let’s hope that’s not the case this time and that this partnership really does help break down the old silos, rather than just reshuffling them. 

Define your roadmap to make the most of the SAP partnerships with Databricks and Snowflake 

The announcements from SAP mark a major shift in how enterprise data platforms can operate with tighter, more seamless integration between SAP’s Business Data Cloud and the leading data platforms; Snowflake and Databricks. While we’re still waiting on the fine print around technical architecture and licensing, the direction is clear: SAP is opening up, and that’s good news for data teams everywhere. 

Now’s the time to start thinking strategically. What does this mean for your current architecture? Where can you reduce duplication, simplify data flows, and unlock more value from your SAP data? Whether you’re already using Snowflake or Databricks, or indeed planning to, it’s worth defining a roadmap to take full advantage of these partnerships. 

Read the official Snowflake press release here. 

Sources: 

https://www.snowflake.com/en/blog/sap-snowflake-partnership-ai-data-cloud

https://www.sap.com/products/data-cloud.html

https://www.snowflake.com/en/blog/sap-snowflake-partnership-ai-data-cloud

Why Digital Transformation MUST start with Data Strategy

Posted on by David Rice

Forbes estimates that a massive 84% of companies fail at digital transformation.  Yet change is inevitable, and those who fail to innovate will get left behind.  Blockbusters, Polaroid and more recently Toys R Us are examples of those that have fallen to the sword of change.  This is why 90% of corporate strategies will list ‘information’ as a critical enterprise asset by 2022 according to Gartner.

So how can we move the needle to deliver more effective Digital Transformation initiatives?  As Warren Buffet once said, “It’s good to learn from your mistakes. It’s better to learn from other people’s mistakes”.  Take the time at the start of the project to research the common pitfalls of Digital Transformation and be deliberate in your planning to avoid them.

Let’s be clear, digital transformation is complex and involves many stakeholders with different objectives, vast webs of complex legacy systems and code and of course requires a shift in mindset and culture.  But here are a couple of things I’ve observed over the years that hinder Digital Transformation initiatives:

Lack of clarity and alignment on goals

It’s absolutely vital to understand the goals of the initiative and how they help the organisation to achieve it’s strategic objectives.  If you are unable to draw a dotted line from what individuals are doing on the ground to the objectives set in the board room, then stop and ask ‘why?’.  Otherwise it’s like running a marathon but not knowing where the finish line is.

Technology first approach

Technology is only a small part of Digital Transformation and with the cloud, it is often the easiest part.  Digital transformation is about intelligent use of ‘information’ to drive better ‘outcomes’.  Yet we often forget about the ‘Information’ and the ‘outcomes’, and just look at the technology.  Maybe this is because it’s the easy bit, the one that the technical team that’s been hired is more familiar with.  Focus on outcomes and ‘Information’.  That’s where data strategy comes in!

Data Strategy

I hear so much talk in the corridors of large corporates about the latest AI (Artificial Intelligence) or ML (Machine Learning) initiative or how the organisation is using RPA (Robotic Process Automation) or IoT (Internet of Things).  But I hear far less about Data Governance, Data Quality, Data Catalogues and Data Literacy. 

Yet IoT, Automation, AI & ML are underpinned by Data!  Without it they simply do not scale or deliver effective results. 

I often hear the term ‘Data Rich and Information Poor’ but it’s often akin to being ‘Rich’ with counterfeit money (i.e. The ‘data’ isn’t real or of a high quality) so the organisation isn’t really Data Rich at all.  The data is poorly categorised, inconsistent across systems, has no clear ownership and is often undocumented.  This results in mistrust of the technology (whether it is shiny and new or 30 years old), silos of information and poor decisions.

So start your Digital Transformation journey with a data strategy and map out the ‘Information’ required to deliver effective outcomes and how you plan to govern it.  Consider our four pillars, and define where you are right now in terms of people, processes, technology and data.  Ensure you have a team or partners that can bring people on the journey, create clarity around the outcomes and deliver solutions that truly scale.

The four pillars of a data strategy

Posted on by David Rice

Mention data to some executives and you’ll get a range of reactions, ranging from evangelical to utterly perplexed. The latter group might know data is important to their business and understand that using it correctly can bring significant wins, but there is often considerable confusion over how to best implement it. Fret no more, as here are the four pillars you need to launch a successful data strategy. 

People 

First look around your organisation and assess existing strengths and weaknesses. Do your staff understand the power and value of data? You don’t necessarily have to run out and employ a team of experts, instead audit existing skills. If somebody is a whizz with an Excel spreadsheet, chances are you can train them up to become more data literate.   

Next take a step back and look at the structure of your organisation. Is there a divide between your IT department and your business people? If so, that needs rectifying. To get the most out of your data, everyone needs to work together. Rather than make it the sole preserve of techies, a joined up approach will spread the responsibility and offer the best chance of creating a successful data culture. 

Process 

One of the quickest wins is in the optimisation of existing business processes. One company we worked with wanted to create a more efficient system for posting journals in their finance system. At the time they had a 20 step process for this seemingly straightforward procedure; laboriously copying information into Excel, running four different reports, then ticking off a long paper checklist before finally posting. Through automation we were able to reduce that process down to two or three steps, while still allowing for all important checks to take place. 

Ensure automation is built into your data systems. It will transform the working lives of even the most data-phobic employees, providing alerts on anything from fluctuations in sales to customer complaints. Rather than finding out about this in the annual report or having to dig through the data for answers, a simple warning symbol in your regular reporting will alert you to potential problems before they cause too much damage.    

Data 

While it’s important to have everyone on board, it is crucial to have trusted individuals overseeing data in areas such as customer and product information. You need people who can own that data and be responsible for it. Ensure that they have clear strategies around managing data quality and data governance. This stuff is as important to growing your business as your staff and product – treat it with the same care and you’ll reap the rewards. 

Technology 

Once you have thought through all areas of your strategy, only then should you commit to spending money on the necessary tech. We often meet companies who have muddled through by bolting on extra systems here and there. What they should have done is to step back and ask whether it might be simpler and more efficient to just start from scratch? Often building on a legacy system is a false economy, while investing in the correct, modern system for your needs will save you time and money. 

If you take just one thing away from this, it’s that upfront thinking is absolutely crucial. We see so many companies who have taken bad advice and invested in a pricey data lake or warehouse that ultimately didn’t serve their needs. They then have to start over, or are forced to work with compromised systems. Never overlook the importance of starting with a defined data strategy, it is one of the most important business decisions you will ever make. 

What better way to kick of you data strategy that a FREE 90 minute Data Strategy workshop tailored to your business? Book your call with one of our data gurus now to understand how data can help you to achieve your goals:

https://meetings.hubspot.com/david-rice2/free-90-minute-data-strategy-call