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If you work with data you may have heard of an information layer, but what is it and why are people talking about them? In this blog, we’ll explore the meaning of the term, as well as why it’s important and how it could help your organisation. What is an information Layer? An information layer is a repository of business-critical data that is automatically sourced, quality assured (with an audit trail), and combined into a shareable, ready-to-use, up-to-date table. This means that data only needs to be sourced, stewarded and engineered once, yet it can be used in multiple ways, whether it be a dashboard, an application, or a report.  Much like sugar refining, an information layer is taking something raw, (in this case data instead of a sugarbeet) and making it usable in many applications the way refined sugar can be

Many data leaders say that a data culture is critical in becoming a data-driven company. But what exactly does it mean, and why is it so important? We'll break it down for you below. What is data culture? Data culture is a mindset within an organisation. The objective of a data culture is to encourage the people in an organisation to utilise, understand and promote data in the everyday running of the business. Creating a data culture emphasises the importance of data in decision-making for all aspects of an organisation, in all departments. Why is data culture important? This year's survey of data leaders by NewVantage Partners identified cultural factors as 'the greatest barrier to organisations becoming data-driven'. While most companies have the necessary technology, creating the cultural change required to put data at the centre of decision-making is a much greater challenge. Encouraging

Digitisation, digitalisation and digital transformation may sound similar and are often used interchangeably, however, they have different meanings with important distinctions. These words are seen a lot, but what exactly do they mean? How are they different? And why does it matter? We’ve broken down the terms below. Digitisation Digitisation is the process of taking something analogue and making it digital. Many companies digitise when moving from a physical filing system to a digital one - for example, scanning customer information and storing it in a cloud rather than a paper system. Digitisation is a great way to preserve data and information and makes it easier to access and search. Digitalisation Digitalisation is a step further where you now take any data or process and use digital innovations to make them more useful to your company. Digitalisation is more than making information digital, it’s

We often hear data literacy mentioned as an important step in the data-driven process. Often used to refer to the education of ‘non-data’ employees, we know that data literacy is about upskilling groups of employees, but what does it mean in practice? And what is the impact of engaging in a data literacy program? What is data literacy? At its core, data literacy is removing the fear of data with knowledge and creating a mindset to embrace data innovation. A ‘data-literate’ employee is able to understand and use data with confidence in their daily role, communicate successfully about data concepts and collaborate on designing data products.  A workforce that is not ‘data literate’, may face challenges in data transformation due to a lack of engagement from business teams. This can impede collaboration on data projects, resulting in misinformed project briefs, slowed implementation and

The latest advice for companies striving to become data-driven is to ‘manage data as an asset’. But what does that actually mean? In this article, we’ll dive into what it means to have ‘data assets’, why you need them, and how to manage them effectively. What does it mean to manage ‘data as an asset’? Data creates value for a company. It’s utilised to inform business decisions, and draw insights that can translate into profit for an organisation.  Data can be as much of an asset as the people, inventory or technology that a company owns. However, many businesses still treat it as a by-product, leaving their data in an ‘unrefined’ state where it is of limited value.  To manage data as an asset is to adopt essential principles for that data that you would apply to any asset or resource, e.g. understanding the

There’s a lot of intel out there on how to get the most of your data. So much so, that some days it’s difficult to navigate the buzzwords and trends In this article, we’re cutting through the confusion to explain some core data concepts and explain how to use the ‘product’ method to connect data solutions to the business tasks that are completed, so you can increase company productivity and performance.  What are data products? A data product is a specific process or solution that uses data to address a specific need. Google flight alerts are a perfect example of a data product as they use data to notify consumers via email when flights of interest drop in price. It’s a great ‘data product’ because it’s completely aligned with the user’s needs, delivering precise information via a method that’s time-sensitive and on-demand. Is that

Data can be an intimidating subject, full of complexity and jargon. As a result, many business people we work with hold back on joining the conversation, as they’re worried they don’t have the expertise. In reality, data is just information. Business people generate this information in their day-to-day routines, and as a result, are actually in the best position to contribute value to the data conversation. Minimizing complexity in data discussions At Think Evolve Solve, our team has a blend of data analysts, engineers and scientists. But it also has business people from sales, marketing & executive roles. We help organisations build the most value into their data projects by engaging both business teams and technical teams in conversations about data. The simple questions below enable us to cut the complexity and be specific. Are you talking about data itself, or a data solution? Data is

Despite significant investments into data initiatives, many large organisations are not getting everything they want from the data in their organisation, and still have some way to go to meet their data objectives.  The 2021 New Vantage Big Data and AI Executive Survey of 85 Fortune 100 executives found that just under a quarter (24%) of respondents say they have ‘created a data-driven organisation’. Despite 99% of respondents having made a significant investment in data initiatives such as Big Data and AI, only a third (30%) of respondents agree that they ‘have a well-articulated data strategy’.  The biggest struggle many firms face is not related to technology limitations but cultural barriers, with 92.2% of respondents identifying people, business processes, and culture as the biggest challenge to becoming data-driven. This is having a distinct effect on data outcomes, with just a third of respondents (29.2%)

Despite increasing investment, many companies are struggling to maintain momentum in their data strategies. A recent survey from TechCrunch states that 72% of large companies haven’t been able to create a data-driven culture.  With many organisations devoting more and more resources to their data strategy, this isn’t due to a lack of trying, however the sheer scale, complexity and number of employees at large organisations can often disrupt successful strategy implementation.  Here are some of the common challenges companies encounter on the journey to becoming a data-driven organisation.  Accessibility & Autonomy There’s a big difference between making technology available to employees and having them embrace it. One of the first challenges companies address is how to make data available in a secure way for staff to use, as demonstrated in a recent study cited by  Harvard Business Review that saw 77% of executives report