Top tips to get more from your data

28 June 2022

Data is all around us. Your organisation has plenty of it, but are you using it to its full potential? 

Businesses that successfully harness their data are the innovators and leaders of their industries. By using data to strengthen business processes, streamline workflows and find out more about their customers, they can increase sales and boost ROI on their tech spend. 

Whatever the reason is for you to do more with your data, here are the fundamentals you need to know before getting your project off the ground.

Understand the questions you are trying to answer. What is it that you are trying to achieve? Get a real sense of what you want data to do for your organisation. Once you focus on what you want to do, you can start to see what the data capabilities look like. From there, you can define your questions and targets. Do you want to identify your top-performing stores? Do you want to know how many people actually work in the office? Or maybe you want to use data to track how many people use your customer service feature on your mobile app compared to your call centres. Like any journey, you need to know where you are going before you start – and the same applies to success with your data. 

Know how to measure your KPIs. When talking about the value of data, we are often talking about spotting patterns and trends through data analytics. What is the data telling us? What is happening to impact KPIs? Most businesses that work with data have a comprehensive overview of descriptive analytics – the process of using data to identify trends and relationships. However, those that don’t have joined-up information might have a good understanding of revenue metrics, but miss the mark with delivery, manufacturing or operations, meaning they risk falling behind in optimisation and efficiency. Get the metrics right, so you can start to analyse and ask why

Improve data transparency. By bringing together information from across the business together in one place, the simpler it becomes to collaborate across different teams, driving innovation and new insights. To begin your journey towards data transparency, you need to get your data organised. We suggest you list all your data sources and implement Data Ingestion and Warehousing. Next, pull different data sets from all types of interfaces into one central location. Then you can create Data Pipelines and send them to an analytics platform for further analysing. This will take your data project to the next level.

Don’t just collect data. Analytics and visualisation tools, such as BigQuery and Looker, help us go back and answer our business questions. ‘Why were our Saturday orders lower than normal? Was it because our staff levels were low? That might explain why Saturday had a 50% drop in revenue.’ These tools help us bring data together in an accessible, easy-to-digest way that allows us to make connections with past and present information. Data can be set up to automatically update in visualisation tools so dashboards are constantly relevant and the quality of your findings improves. Whilst it is possible to do it in-house, Netpremacy is here to help you accelerate this part of the journey.

Build a data-driven mindset. Start with the management team. Set expectations from the top down with decisions focused around data. Then, you can get everyone in the business involved. Empower your teams, from Marketing to HR, not just the Analysts and Data Scientists. Do this by bringing concepts to life with real-time dashboards to give the exec team an instant vision for how this data mindset can expand across the business. By building a culture around data, everyone can use it to enhance their daily work, whether that contributes to revenue growth or makes tasks more streamlined and efficient. 

These simple steps are the foundations of any data project. But more often than not, they get overlooked. The data world can be very overwhelming. After all, we create 2,500,000 terabytes of data every day. The good news is that any organisation can use data to their advantage. Data-driven companies are 58% more likely to exceed their revenue goals when compared to their non-data-driven peers. So act now and start to turn your data and analytics ambitions into reality.

21 June 2021

Last Wednesday, Netpremacy ran a closed roundtable where we brought together data decision-makers from the Finance Industry. Heads of Data, Directors of Data, Heads of IT and Chief Data Officers came together, along with our Partners Looker and Google Cloud. We discussed challenges the financial sector faces around data analysis and moving to the cloud and explored ways to help solve them. Here are the key questions we explored:

How do I get buy-in from other business stakeholders for moving our data to the cloud? 

“Start with a strong plan”, recommends Tom Anderson, Technical Consultant at Netpremacy. “Really think about what you need in the cloud, as it is different for every business. You don’t always have to start with a ‘big bang’ (learn more about staged cloud adoption here). You may want to harness data analytics capabilities, scale at speed, or improve your data protection. By taking small steps and delivering Proof of Concepts along the way, you can prove yourself in the business and start to build the momentum you need to reimagine your business in the cloud.”   

Security is key for us, so how can Google provide reassurance that this is a safer option than on-prem?

Realistically, how much can your organisation afford to spend (time, money and testing) on security in comparison to Google? Is your data really more secure on-premises than in the cloud? It will be part of your role as a data leader in the business to reassure others, but Google Cloud can provide plenty of documentation, case studies and advice to help you. One attendee also suggested this is a key area to bring in experts that can help you with penetration testing and making sure you have all the right foundations in place. 

How can I change the business culture to be more data-savvy?

Ensure everyone in the business understands the value of data and the benefits they’ll enjoy by using the tools and processes you implement. One of the top tips from Looker is to identify frequently asked questions from your data team and focus on answering those first, as they’re clearly the ones the business needs. By using a data analytics tool like Looker, you can empower business users to answer questions they have about data themselves rather than relying on the data team – encouraging more data-driven decisions. If more people can take ownership of data, you can start to grow an appreciation for what can be done with data. This way, you will have business and tech leaders working together, hand in hand. Businesses getting ahead are those where the membrane between business and technology teams is dissolving.

Sounds good in practice, but what about the reality?

It’s all well and good for technical companies or cloud-first FinTechs, where there’s some expectation of non-technical users to use no-code or low-code solutions, but what about established businesses with even more established spreadsheets? James Tromans, Technical Director, Office of the CTO at Google Cloud has plenty of experience with ‘the spreadsheet issue’. “Show, don’t tell”, he advised, “find something their spreadsheet can’t currently do that your solution can. Once they start to see what’s possible, their imagination will ignite and they’ll soon be on board.” 

It was interesting to hear the challenges these key players face when contrasted against some of their younger FinTech competitors’ that we discussed back at our roundtable in April (read more here). Despite the differences, the main challenge they both face is cultural change. It is now a test for technologists within any business to take up more of an evangelist role and continually prove themselves. If this is something you are struggling with, we recommend seeking help from an experienced partner with plenty of experience advocating for technical change. Businesses such as Google and Looker can further help you make your case with key documentation and use cases from the industry. 

Speak with the Experts

At Netpremacy, we have extensive knowledge and experience in helping organisations on their cloud journey, whether that’s on a consultative basis or delivering an innovative transformation to your business. If you’d like to get more from your data, our team of data engineers and infrastructure specialists can help. Our decade of experience in change management means that you’re in safe hands to make the cultural shift needed to change your organisation. Contact us for an initial conversation on your data strategy to start doing things differently.


Read More:


Looker & Google Cloud’s data analytics platform provides more options to help you deliver more through the use of strong, fresh insights.


Monzo Case Study 

Monzo refines and optimizes its fast-developing product with BI analytics based on Google BigQuery and Google Cloud Platform.


Photo by Burst on Pexels

09 June 2021

Using data to make informed business decisions


Back in April, we brought together key players in the FinTech start-up space for a closed roundtable. CTOs, Heads of Data and Heads of Engineering spoke to Netpremacy and our partners at Looker and Google about data areas they wish to improve in their businesses. 

We discussed the challenges that arise when using data to drive smarter business outcomes and how to address them. Here’s what we learnt. 

What data challenges do leaders in FinTech face? 

Despite a universal understanding amongst the group of data’s value and an appetite to use it to its full potential, several barriers are getting in the way of making this happen. 

A lack of data transparency. Thanks to a wide range of data sources, environments and a reluctance to open up data to everyone, it can be challenging to centralise data in an accessible, meaningful way. 

Getting started in making more data-driven decisions. Many companies have large amounts of data but are unsure how to capitalise on it and make educated business decisions based on their findings. There is pressure to do more with data, but the myriad of potential can be overwhelming. 

Creating a data-driven culture. Even where there are data analytics tools in place, they are just part of the picture. How do companies make sure that end-users not only understand how to use the tools at their disposal but use data to drive what they do? How do they encourage everyone in the organisation to take a more data-centric approach to understand the business better and use insights to improve customer experience?

Driving adoption of self-service data. Data queries and requests to the technical team can cause bottlenecks and block gaining valuable insights in customer activity, product opportunities and more. How can businesses encourage non-technical users to discover these insights for themselves?

Modernising reporting across teams. Many companies in the FinTech space are struggling with updating the way that their teams are creating reports. The spreadsheet culture is still predominant in many workplaces. It causes a loss of data and leaves room for human error. It also slows down the reporting process due to the manual importation of data. 

So, how to solve them?

Here are just some of the ideas we discussed with our panel, Looker specialist Colin Murphy and Matthew Yeager, EMEA Technical Programme Lead, Startup & VC Ecosystem at Google. 

Get buy-in by solving the right problems and speaking the right language. As well as being Google’s EMEA Technical Programme Lead, Matthew Yeager has plenty of experience in the start-up arena, with multiple start-up successes to his name. His advice, when at the start of a business journey is to ‘ask yourself, what problem am I trying to solve here? For example, how can I manage my cash flow better? How would knowing more about my data help fix this problem? Use language that resonates across the business. You need to be able to describe problems and possible solutions in a way that appeals to the right people at the right time, from investors to the C-Suite, and everyone in between.’

Do your research. Don’t just rely on your data, use other research data sets to learn more. Google has a free open data set for you to go and explore. Finding out what people are searching for will help you produce a product that fits a gap in the market. Read what others, such as challenger bank Monzo, are doing with their data to get ahead. 

There is no such thing as too much data, but stop waiting for ‘perfect data’ to get started. It is vital to have a working theory with a data set. The more data you have, the better and more valuable insights you are going to get. Throwing away data can harm your analysis and outcomes. However, waiting for the ‘right’ or ‘perfect’ amount is fruitless. Use the data you have right now, and keep collecting more to ingest and improve your model.

Let the platform do the work for you. Another piece of advice from Matthew was to stop trying to write ‘pretty code’. No investor is interested in machine learning code or how good it looks. Investors only want to know what problem you are solving. Save time by using tools to analyse data quickly. 

Create a model that allows anyone in the organisation to gain data insights. Move away from a model where the technical team is writing a requested query to answer one question at a time by empowering the end-user and reducing bottlenecks with tools like Looker. For example, Monzo’s non-technical staff self-serve 85% of BI queries without consulting the data team with their BI solution built on Google BigQuery and Google Cloud Platform. 

Bring non-technical colleagues on the data journey with you. Ease colleagues gently and at their own pace. Start an end-user with a dashboard, then go beyond that dashboard to build out their own visuals, insights and more. Train your new starters on tools like Looker so they understand data is as much a part of their role as their technical colleagues’. Be open to and appreciate their feedback and ideas, don’t be overly prescriptive. They will use data in a way a data engineer/scientist wouldn’t, but that can be where the real insights happen. 

Integrate technical and end-user teams. Encourage a spirit of data-driven working and a feedback loop by bringing together technical and end-user colleagues. Technical colleagues can upskill and help their non-technical colleagues, and non-technical staff can give insight into the practical application of data insights. By working side-by-side, teams can work together to get better results for customers and the business, truly driving innovation. 

What next?

As FinTech companies grow, so does the amount of data they are storing and collecting. This valuable, often untapped resource can be the difference between just another failed startup and a massive success. Using data to understand customer behaviour, predict trends and future demands is already the norm for forward-thinking companies.

Wherever you are on your data journey, there are plenty of powerful tools like Looker and Google BigQuery to support your company in accessing and gaining insights into data. However, as many are learning, the real challenge is company culture. Giving non-technical colleagues the technology they need is one thing, but pivoting to a data-led approach is a must if your business is seriously committed to being one step ahead of the competition.  

Speak with the Experts

At Netpremacy, we have a plethora of experience working with hyper-growth companies, including Just Eat, Monzo and Deliveroo. If you’d like to get more from your data, our team of data engineers and infrastructure specialists can help. Our decade of experience in change management means that you’re in safe hands to make the cultural shift needed to change your organisation. Contact us for an initial conversation on your data strategy to start doing things differently. 


Read More:


Looker & Google Cloud’s data analytics platform provides more options to help you deliver more through the use of strong, fresh insights.



Monzo Case Study 

Monzo refines and optimizes its fast-developing product with BI analytics based on Google BigQuery and Google Cloud Platform.



Photo by Essow from Pexels

02 June 2021

Alastair Lumley

Alastair Lumley – Digital Native & Finance Lead, Netpremacy

Last week I attended Google Cloud’s Financial Services Summit to learn from Google experts and others from across the industry on what the future holds for the Finance Industry. I discovered how Google Cloud is driving real change and helping to reshape the industry, from modernising more traditional businesses to supporting the challenger banks. 

Straight from the opening keynote, Google made it pretty clear that Financial Services are a huge focus area for them. They are currently dealing with some of the largest financial institutions globally, including HSBC and Deutsche Bank. This experience is helping them to shape and evolve their cloud services to better meet the needs of the industry. This had led to them becoming the only cloud provider to develop focused and dedicated services for the Financial industry,  two of which were launched at the summit – Lending Doc AI and DataShare.

Google also highlighted their three key focus areas within the financial industry; accelerating omnichannel experiences, using data and analytics to transform businesses and modernising core operations in banking and payments. These were covered in the different streams run on the day, including Banking, Capital markets, Insurance and Payments. We heard from Deutsche Bank on how cloud services have driven innovation, how PayPal used them to weather the Covid storm and how BNY Mellon constantly evolves, attracts the best talent and adapts to new challenges. You can watch the on-demand sessions here.

Event Round-Up

The key theme of the summit was how Cloud Computing is enabling the Financial Services industry to innovate and react to consumer demands and specifically how Google Cloud is the go-to strategic partner for the industry to drive this type of change. 

One session I found particularly interesting covered how Google and HSBC are currently working together to make banking more sustainable and lower their environmental impact. Work so far included evaluating supply chains, identifying where they are most economical and sustainable and exploring ways to improve this. Taking experience from both sides of the table – a global retail bank with vast knowledge of supporting businesses of all shapes and sizes, and combining that with Google who understands how to problem solve using innovation….one to keep an eye on! 

Another fascinating discussion was how banks are helping to improve the house buying process. The key learning was to avoid using technology for the sake of it and automate an existing bad process – we should use it to drive change.  The house buying process is one of the most complex and emotionally stressful purchases you’ll ever make so a lot of focus is now going into how can this become more enjoyable and how can technology play a pivotal role in this. 

There were many more sessions covered such as how we can activate a data strategy in insurance by leveraging Google’s products and its partner network to start and implement these projects, all the way through to how innovation in the financial industry can help innovation in other industries.

Key Takeaways

Financial organisations globally are leveraging cloud technologies to innovate and provide better solutions to challenges, better services to customers and become more economically and socially responsible. Google is actively helping drive this change and developing solutions focused on the financial services industry by engaging and supporting some of the largest institutions globally. 

Each journey is different and will have its own goals and outcomes, but the opportunity for any organisation to transform and drive change is there. From using data to improve customer understanding, fighting against fraud and leveraging scalable cloud infrastructure to meet spikes in demands, what is important across the board is the correct support, partner and technology along the way. 

That’s where Google and Netpremacy can help. By understanding what it is you want to achieve, helping define and build plans and strategies around the technology, you can reach your desired aims and objectives much faster, in a way that future-proofs your success. 

To hear more about how to transform your organisation, or to register an interest in our upcoming roundtable for Financial Services, email me


03 March 2021

Democratising data is a hot topic, and is helping businesses to get ahead of their competitors, here’s how…

If 10-15 years ago you’d have asked a bank “would you ever think of giving 90% of the workforce access to all of your data?” the chances are you’d have got a pretty blunt reply. 

Fast forward 10 years, and we see a rise in many booming Fintechs, and the stance on accessing data is completely different.

We can learn from Fintech’s.

We MUST learn from Fintech’s to stay current, and successful.

With the introduction of mobile apps and a significantly increased online presence we are a society that now spends the majority of our day online. We’re staring at different web pages, apps, tv screens or mobile devices. This means every interaction is now a chance for us to collect data. It’s giving the likes of Fintechs and cloud first companies the chance to gather a significant amount of data and take customer service to a whole new level.

Cloud technology is integral to this. 

It has helped us rapidly develop new banking platforms, create mobile apps that are used daily, and gather data on every click, swipe, scroll, pause & interaction. 

But how do we use this data for good? How can we ensure the correct teams have access to what they need… The answer is through Democratization. 

Democratization means “the action of making something accessible to all”. If we put this into context this means giving every team in the business access to the data we hold (with all of the correct GDPR & security measures in place). Whether that’s the engineering team, who need to make changes to an app, our customer support team understanding the trending support tickets. It might even be the Exec team trying to define a new strategy and the net product we want to launch. Data democratization is the key to all of this. 

So how do we give everyone access to data easily and when they need it? 

This comes in two parts. 

1.Store your data in a secure and readily accessible platform such Google’s Big Query

2.Visualise and make sense of that data you are storing…introducing Looker 

BigQuery features 

• Analyze petabytes of data in seconds

• Gain insights in a secure & scalable way 

• Access data from multi cloud environments and truly democratise the data 

Looker makes it possible to…

• Use modern BI Analytics to create dynamic dashboards

• Offer a self serve data platform to any department to gain the insights they need 

• Create an environment that can truly leverage everything data has to offer. 

By Leveraging this best in breed technology, businesses are now in a position to give every department their own unique view and access to data. Whether this is to help them to develop a new product, understand the most common support calls coming in, make a decision to enter a new market or offer a new solution. Or, to simply give them access to real-time information. 

As a Google Cloud premier partner Netpremacy is here to help you take data to the next level. There is a range of fantastic tools that can help your company become more transparent with data, and benefit from it. 

We are hosting an exclusive, invite-only roundtable, with key players in the Fintech arena, as well as speakers from Looker and Google. If you would be interested in attending please contact for the private event link and password.

02 December 2020

The energy and utility sector is something most of us take for granted. We pay them for warm showers and to heat our homes, and no doubt we will all be reaching for the thermostat over the long winter months ahead to keep us extra cosy. However, behind the scenes, these companies have to embrace digital transformation and harvest massive amounts of data in order to grow, evolve, and meet the demands of the future. 

The industry is constantly up against challenges; from pressure to reduce emissions, increasing demand, and providing competitive prices to their consumers. Google Cloud has a wide range of industry-leading and energy-specific solutions aimed at helping these businesses digitise faster, and respond to these demands. 

Why data is important for digital transformation

The most valuable asset many companies have is data, and in order to be successful, energy providers must adapt to change, stay current, and realise this. They need to be able to store, read, and analyse data properly, in order to gain a competitive advantage and solve complex business challenges. 

Google’s BigQuery can help businesses bring different data sets together in order to gain those insights, and Google’s AI-powered solutions are the key to unlocking analytics capabilities within your data sets. In this case study, you can learn how Energyworx, an energy supplier in the Netherlands, uses GCP and smart analytics to harvest their data to better plan for future energy demand, and find ways their customers can save on their electricity use. 

If you would like to learn how to use smart analytics to help your business grow and evolve, download our Smart Analytics White Paper here.

A deeper dive into AI and ML energy-specific solutions

Powerful AI models use data analytics to provide actionable insights, and these models can help inspections at scale. This is extremely useful for energy and utility companies who have large areas they need to monitor, such as energy grids, wind farms, or solar panels. Google Cloud’s Visual Inspection solution reduces inspection times without compromising on safety or accuracy and makes organisations more efficient and sustainable. 

Businesses also have the ability to build their own custom Machine Learning model with minimal effort and little to no Machine Learning experience. 

AES is a Fortune 500 global power company that distributes sustainable energy in 15 countries. Their asset inventory is phenomenal, with a value of over £33 billion. They use Machine Learning and drone technology in their wind farms to monitor, manage, and maintain their assets. 

This was the perfect solution, as it was in keeping with their greener vision and they were able to massively scale using Google’s powerful infrastructure. Learn more about their custom made solution powered by Google Cloud’s AutoML Vision here.

For most modern energy and utility companies, contributing to greater customer satisfaction is also an important identifier for success.

AI models like Contact Centre AI allows agents to assist with customer requests more efficiently, leading to shorter call times and improved outcomes, with much quicker resolutions. Learn more about Google Clouds CCAI and how companies are using this technology to modernise.

A smart future for the energy industry

Smart meters are the latest innovation to tackle the biggest challenges facing the industry today. By 2024, almost 77% of EU households will have one installed*. 

This new technology brings multiple benefits such as delivering automated, real-time readings, giving consumers access to their own data; and being able to identify faulty appliances, reducing downtime, and enabling repair staff to be efficient and effective with their time. They also improve the awareness of energy consumption, allowing individual households and businesses to reduce their energy use and generate savings.

Of course, with all new technology advancements, comes an influx of data. Energy companies need a scalable data warehouse to be able to import, process, and anaylse this data. Google Cloud’s BigQuery streams data in real-time and can predict business outcomes with powerful built-in ML models; plus it runs on Google’s infrastructure and is a managed service, meaning companies spend less time developing technology and can focus on their service instead. Read how Halsfund, the largest power company in Norway, uses GCP and BigQuery for the new smart meter network here.

Being a successful energy and utilities company today requires the right technology to solve big business problems. However, in order to truly succeed, you must make the right decisions for your business by making the most of the information you gather.

Now you know what you can do with your data, are you using it to the best of your advantage?

Speak to one of our data experts and we can help you implement this technology and show you how to use it. Contact us here.

*By 2024 almost 77% of EU households will have a smart meter installed, European Commission 


15 October 2020

Christmas is just around the corner…  

With the year coming to a close, and Christmas approaching (yes we are talking about Christmas already), many retailers will already be planning for massive shopping events such as Black Friday and Cyber Monday, and boxing day sales. However, there is no doubt things will be different this year. 

Online shopping is going to explode even more than it already has as we approach a vital time of year for the retail industry. This means more data, more customers, and more manpower. Retail businesses need to prepare for a cyber influx more than in previous years due to the constantly changing lockdown rules and regulations. People are much less likely to be spending their Christmas shopping experience in physical shops, and will be steering towards a safer way of shopping, online. 

Is your marketing as smart as your data?

As we approach the Christmas period, many businesses will have planned a marketing strategy to target their customers, and potential customers, to boost sales and promote special offers. However, many stores will be missing a trick, by not using the powerful AI tools that Google Cloud provides. Storing your new customer database is all well and good, but understanding it correctly with BigQuery is the next step to a more enhanced, and successful marketing strategy. These powerful tools will then be able to understand your data in seconds, and give your business powerful insights into your customer behaviour and predict what to market to your customers before they even know what they want. 

New AI capabilities in Google Cloud means that you can more accurately analyse and understand the data that you are collecting so that you can market in a smarter and more efficient way, based on those particular customers’ spending and behavior patterns when shopping online. Due to the fact that the majority of people will be shopping online this year, it makes sense to invest heavily into your online advertising and marketing campaigns to ensure a maximum ROI

Physical stores are depreciating

It was announced this year that “H&M will close 250 of its 5,000 stores next year as the world’s second-largest clothes retailer seeks to step up investments in its growing online business. CEO Helena Helmersson said sales in September were just 5% lower than last year and the company had returned to profitability after four in five stores were closed at the height of the crisis. Currently, 166 of its stores remain shut.”* This is terrible news for the high street, but means that online sales appear to be the way forward to stay ahead in this industry. 

“A recent study from NRF shows that 59% of consumers will do the majority of their shopping online in time for the holidays – and naturally, you’ll want to give them the best possible experience.”** 

RF President and CEO Matthew Shay said. “Retailers are prepared for an early start to the shopping season, offering discounts earlier to ensure consumers can find the gifts they want, in stock at the price they want to pay, delivered at the time they want to receive them.”**

Although the high street retailers will suffer, there is time to prepare for an inevitably busier Christmas period. 

Storing your data & understanding it in the cloud

Our solutions help you to quickly leverage powerful machine learning algorithms to help gain meaningful insights from your existing product sales history, and much more. This is ideal for customers with no Google Cloud Platform estate, or for those with an existing data warehouse who wish to explore Machine Learning.

Google technology will help you to understand and plan for future inventory stocking levels across various product lines. This is a challenge that most retailers face; striking the appropriate balance between having enough stock on hand to meet customer demand without investing in product lines which are slow to sell, taking up valuable shelf or warehouse space, especially as the demands will begin to increase as we creep further towards Christmas, and the infamous boxing day sales. 

How Netpremacy can help

Our team of data experts can help you to understand the next step into storing and analysing your data to gain the best ROI from the data you have collected. We have a dedicated solution that helps businesses to anticipate customer demand, through the use of Google technology, meaning you will be able to gain more meaningful insights from your data and be able to capitalize on it. This will ultimately lead to better business decisions and a smoother Christmas period. 

Download our custom solution here to find out more, or contact us for more information. 


02 September 2020

Find out how to use Google Cloud technology to anticipate customer demand and gain a competitive advantage


We have put together a solution to help businesses anticipate customer demand, by using Google technology to help gain meaningful insights from their data, leading to better business decisions. Download our One-Pager if you are interested in finding out more about this solution.



To find out more, or to see how your organisation can benefit from this solution, contact us and speak to one of our specialists:

29 July 2020

Understanding Big Data with BigQuery


The way we collect, collate, and analyze data has drastically changed in the last 5 years. Gone are the days when we crammed servers and more servers into our office buildings to hold our information. Cloud computing brought with it a radical change in thinking about the way we collect and visualise the information we hold. Organisations want to know how to understand the data they have and how they can use this data to give themselves a competitive advantage. 

data analysis image

Take the example of Retail. Retailers want to understand: buying patterns and behaviours; who to target at a given time and in what geographic area. Concepts like Data Warehousing, ML, AI and specific products like Google BigQuery are designed to help with that exact business case – by being able to collect and store data about the customer behaviours and analyse it in seconds allows organisations to react fast, and given themselves a competitive advantage in any market. After all, data is the most valuable asset on the planet.

Our question to organisations today is: Are you using your data to your advantage, and if not, what is stopping you?


Businesses are realising the power of data to predict future spending patterns, analyse spending cycles and understand geographical patterns in consumer behaviour. By using analytical tools and AI we can also ensure that if we are to enter times of uncertainty again, we can initiate and ensure our business continuity plans are in line with the insights our data has provided us. Google is often considered the market leader in data analytics capabilities, with a specific focus on its solution, BigQuery. BigQuery is your enterprise data warehouse, fully managed and completely serverless with built-in machine learning capabilities and is at the forefront of the innovative organisations that are using analytics to gain competitive advantage. Providing usable and easy to digest information is a must and BigQuery can run analytics at scale with 26%–34% lower three-year TCO than cloud data warehouse alternatives. Being resilient, scalable and cost-effective has provided customers with faith in Google Cloud services and there are many more benefits to this solution, click here to understand more about BigQuery. 

What we want to understand is the use of BigQuery, some real-world data scenarios where companies have invested and had a tangible return by using this service to collect and understand the data they receive, and how partners like Netpremacy can assist you. 

So with this in mind, let’s look at the example of how Enterprise organisations with multinational functions are using Google Cloud and Big Query. UPS are world-leading distribution organisation with a global footprint, but the perspective of their operations is definitely needed to understand the scale of this operation:

• Every day, UPS delivers 21 million packages in more than 220 countries worldwide. During the all-important holiday season, the number of packages delivered per day can reach its peak.

• The drivers who make that possible perform 120 pickups and dropoffs daily.

• The number of possible routes each driver can take from stop number one to stop number 120 is unthinkably large at 199 digits.


UPS set out to use Google Cloud Platform (GCP) to design routing software that saved them on average $400 million per annum. GCP provided the platform scalability and security and BigQuery provided the machine learning to fundamentally change their operations in line with their data insights. The information they gained from that data help inform UPS on how to load delivery vehicles, make more targeted operations adjustments, and minimize forecast uncertainty, especially around the holiday seasons. Ultimately helping the organisation deliver more packages at a lower cost which in turn maximised their ROI. 

Although the process of moving to the cloud, or setting up a data warehouse with BigQuery may sound daunting, Netpremacy are here to help. We can be your trusted advisors and partner throughout the whole process – from the initial stages exploring Google Cloud Platform services; to the commercial, deployment and aftercare of workloads. We help optimises spend throughout to ensure you are utilising your Google Platform at peak efficiency. Many data strategies start small and leverage the scale and power of Google to grow. No matter the size of the data you house, the information you gain will continue to grow. So even though most organisation’s data is not on the Petabyte scale, Big Data definitely starts with collecting lots of Small Data, and analysing that data to gain valuable insight is vital for organisations to move forward ahead of their competitors.


If you could analyse data, fast, concisely, with zero operational overhead and a helping hand from a Google Premier Partner, why wouldn’t you?


We are running a number of data related webinars over the course of July 2020, for our current customers and to organisations that want to find out further information surrounding Big Data and BigQuery. No matter the vertical or size of your organisation, data-driven strategies are vital to the success of your business in new and digital environments that we now face more than ever. Get in touch with our teams today. Or contact

11 May 2020

Learn about our 3-step strategy for getting the most out of your data


Now more than ever data is becoming one of our most valuable and most governed assets. Data is all around us and it’s something that we are all using to our advantage. Such is our dependency on data and understanding it, we have teams dedicated to analyzing it, understanding it, dissecting it, predicting it…. The list goes on.

The tools at our disposal are endless and the skill set of data scientists and engineers is constantly growing and improving. However, one thing that is often overlooked, and is potentially the most important thing to consider and understand is actually, what do we want to know? And how do we build a strategy to help us get the most out of our data? 

Netpremacy is Google’s 2019 Global Partner of the Year for Work Transformation Enterprise. Our work over the past decade has been dedicated to understanding organisations’ longer-term strategies, understanding what’s driving some of the world’s leading brands, and how data is beginning to play a significant role in this. This ranges from the tools they use for collaboration and innovation all the way to a fully functional data strategy. Our large team of engineers are extremely skilled in the use of Google’s analytics tools and helping identify and build out a longer-term data strategy.

Below are some of our top tips on how to build a data strategy, and what to look out for along the way. 

Step 1: Understand the business & look for a quick success

Before we even begin to look at what new tools we can use, it’s integral we understand what direction the business is going in. 

  • Are we looking to increase online sales by 20%? 
  • Are we looking to enter a new market? 
  • Are we striving for better operational efficiency? 

Once we understand the direction of the business we can identify what we need to know and the questions we want to ask. We’ve found having 4-5 initial use cases or problems to solve builds a good foundation for a proof-of-concept or pilot programme to get started.  

For a lot of organisations, this can be a new concept and something that needs traction within the business, as when done correctly and with complete buy-in from the business, the benefits can be staggering. 

Now we’ve identified the direction of the business, it’s time to choose a problem that can be solved relatively quickly and easily, but will have a big impact on stakeholders across the business. That could be simply understanding buying trends for a specific demographic & building a view of the customer. Once we have a level of trust and success in the business it’s much easier to find new use cases, funding, and momentum to keep the data strategy going. 

Step 2: The Requirements & Governance 

Once the areas where we can have the quickest and immediate impact have been identified, what will really help us gain momentum internally is to understand what data we need:

  • What types of data are we going to capture and work with? Think Structured vs Unstructured, Transactional, or Relational data. 
  • Do we need to augment what we currently have to supplement the analytics we can run? 
  • What sources of data do we have in the organisation?
  • Read our blog on BigData to learn more

Understanding this is key as without the right data and quality the outcomes will be heavily impacted and could make or break any long term data strategy before it gets started.

As mentioned at the start of this blog, data is quickly becoming one of the most governed and controlled assets in the world and with new regulations such as GDPR its integral that we have the correct governance in place. This means truly understanding the data we hold, is it secure? Do we need permission to use it? Who is responsible for it, How do we keep it up to date? 

Step 3 – Skillset and technology

Finally, we understand the strategy of the business, we know what data we have and the governance around it. We can now look at what technology we want to use and who is actually going to use it. Do we have the resource in house? Are we lucky enough to have skilled data engineers waiting for a project to come up and the technical resource to house petabytes of data, query it in seconds, and get an answer? The chances are probably not! But we can work on building the internal capabilities, as there is a significant increase in training courses, qualifications & employees who understand data and can leverage a wealth of different technologies to better gain insights from the data we have

We also need to take into account where this data is going to sit. Do we have the infrastructure to do this all in house? Unlikely! 

This is where cloud providers like Google Cloud come into play. 

As we are looking at housing and querying large quantities of data that are constantly changing and growing, we need the correct environment. We need to be agile, adaptable & make sense of data quickly in order to get the maximum impact across the business. This is why the majority of companies are choosing public clouds such as Google Cloud Platform and using tools like BigQuery to help them. 

We’re lowering IT overheads as we don’t need dedicated local hardware. We don’t need to build our own complex analytics tools. We can simply use the market-leading tools available, make sense of petabytes of data in seconds, and then use this to have a positive impact on the business. 

Sounds simple right? 

These strategies can get extremely complex when we start trying to please everyone, and we need to tread carefully or the use cases will grow and the complexity grows with them. This is where a well thought out and constructed strategy comes in and helps keep us on track.

Netpremacy is uniquely placed to help when it comes to creating data strategies and implementing them. Over the years we’ve understood what makes a successful strategy, built up a team of dedicated engineers who are experienced in Google’s Cloud Platform & have implemented some of the largest data strategies and projects spanning multiple verticals from Retail all the way to Energy & Utilities. 


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