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You’ve probably heard the saying, “It’s not what you have, it’s how you use it.” Never is this potentially more true than when we’re dealing with data.
Data is a collection of facts and information turned into a form that’s easier for us to process. It can be numbers, words, measurements or even just observations. Consumer data often holds many insights about your customers – from what they like to buy to how or even when – and can help us build more positive customer relationships.
Gathering consumer data, however, is only one part of the equation – what matters most is how you use it. In today’s tech-led world we are being overwhelmed with data, and if you don’t know what to do with it, your competition will.
Here at Bespoke, we help businesses efficiently process their data to unlock powerful advantages. We do this in five ways:
Data transformation involves changing the format, structure, or values of raw data in order to make it easier to process (see below). It may be constructive (like adding or replicating data), destructive (deleting records and folders), aesthetic (standardising values and labels), or structural (such as moving and combining columns in a database).
We transform data to make it more organised and easier for both humans and computers to use. It helps to improve data quality later down the line (see Data Validation) and protects against potential problems like null values, unexpected duplicates or incompatible formats.
Data transformation might also include data integration – the combination of technical and business processes to combine data from various sources into meaningful and valuable information.
All of these transformative processes are crucial to effective data management, which is the practice of collecting, keeping and using data securely and cost-effectively.
More data of course means more processing, which can significantly add to your company’s workload. That’s where data automation comes in.
Data automation allows mundane data handling tasks to be run effortlessly in the background, without demanding precious employee time. It can be achieved using business applications such as Excel and Power BI, or even a bespoke solution created specifically for you.
Different types of data automation might include data capture automation (making it easier to collect, store and organise large amounts of data at once); automating business processes or workflows, and automated data uploads (leading to increased accuracy and saved time).
Data visualisation is the presentation of data in a graph, chart, diagram or other visual format. It is incredibly important for business dashboards as a way to communicate relationships between the data and allow trends and patterns to be easily seen. Machine learning makes it easier to conduct business analytics such as predictive analysis, which can then serve as helpful insights for future goals.
Data virtualisation, meanwhile, allows an application to retrieve and manipulate data without requiring technical details such as the data’s format or physical location. Similar to data visualisation, the goal of data virtualisation is to create a single representation of data from multiple, disparate sources, without having to copy or move the data.
Data processing is when data is collected and translated into usable information. It is important for this to be done correctly so as to avoid negatively affecting the end data or product.
Starting with the data in its rawest form, data processing converts it into a more readable format (such as a graphs or documents, etc.), enabling company employees and stakeholders to utilise the data for their own data analytics projects.
This type of information processing is typically done using machine learning algorithms, though the process may vary depending on the source of data being processed and its intended use.
Data validation involves checking the accuracy and quality of source data before using, importing or otherwise processing data. When moving and merging data from different sources and repositories, it’s important to make sure it conforms to business rules and doesn’t become corrupted due to inconsistencies. The goal is to create data that is consistent, accurate and complete, to prevent data loss and errors during a move.
Different types of validation depend on destination constraints or objectives. Data validation is also a form of data cleansing.
At Bespoke, we have a team ready to help you prepare to work with your data and understand the opportunities available and even do a data healthcheck. Just shoot us an email to set up your free consultation.
In a world of ‘big data’ and information, more and more businesses are striving towards digital transformation as a way to keep up with the ever-changing technological landscape.
So what exactly is digital transformation and why should you be making it a focus for 2021? Here, we’ve outlined everything you need to know about this increasing business trend.
Digital transformation has taken on many meanings in today’s digital era of big data and data management. The truth is, it’s a term that can mean multiple things to different businesses, depending on a company’s main priorities and overarching end goal.
Broadly speaking, digital transformation is the practice of integrating digital technology into all areas of a business, significantly changing how it operates and provides value to customers. In doing this, digital transformation also requires businesses to rethink old models, become more agile in responding to new problems, get comfortable with failure and continually challenge the status quo.
According to Jay Ferro, CIO of Quikrete, digital transformation should begin with “a problem statement, clear opportunity, or an aspirational goal” – basically, your company’s ‘why’. This could revolve around improving customer experience or increasing productivity, or something more aspirational, like becoming the absolute best in your industry using new digital technologies you didn’t have years ago.
There are several reasons a business may decide to take on a project of digital transformation. But for many, the most basic and common reason is survival – they simply have to.
An organisation’s ability to adapt quickly to potential manufacturing disruptions, market pressures and changing customer demands is critical to its long-term success. This has become even more apparent in the wake of the covid-19 pandemic, when consumer habits shifted dramatically and businesses were faced with totally new and unprecedented challenges.
Recent studies show that increasingly the digital transformation process is being viewed as a long-term investment, with relevant initiatives set to take over a 50% share of worldwide technology investment by 2023. Technology is no longer just a choice – it’s a fundamental business strategy that must be part of wider operative-initiatives.
Five common ways that digital transformation can help your business are:
As just mentioned, data and analytics can play a key role in an organisation’s digital transformation efforts. Stats show that fewer than 50% of documented corporate strategies mention data and analytics as essential components for delivering enterprise value, according to Gartner, but this is changing. By 2022, it is predicted that 90% of corporate strategies will mention big data and analytics as a critical enterprise asset.
The answer, therefore, is clear: data and analytics competency should be paramount within your business for digital transformation success. This means defining a strong data strategy and implementing the relevant data transformation methods in order to make the absolute most of the information available.
Leading organisations in various industries are wielding data and analytics as competitive weapons, using them to accelerate growth and inspire innovation. But many companies still struggle under the weight of their traditional business models and processes that may not allow for the potential that data and analytics can bring. Others may also not be able to make the cultural shift needed to work with big data, or commit to the information management and analytics skills needed to truly make the most of its power.
Here at Bespoke, we provide various solutions to help you transform your data strategy. From direct consultancy to our range of out-of-the-box automation and analysis tools, we can guide you every step of the way towards making the most of big data. Simply get in touch to arrange a free initial consultation with one of our experts.
It wouldn’t be entirely surprising for companies to ask: is there an end to digital transformation? How can we know when we have reached it? When will we be able to say we have truly achieved digital transformation?
A more relevant question might be, what comes after digital transformation? Is there a next phase, and what will we call it?
Gartner has named the period beyond digital transformation as the ‘ContinuousNext’, which will reflect the capabilities all companies need to keep up with the continuous change driven by technology.
ContinuousNext is a formula for success in a world that is constantly changing…”through and beyond digital transformation”. Meanwhile, Accenture is naming this period as the “post-digital era”.
Overall however, industry experts agree that digital transformation is a continuous process, as technology will always continue to advance rapidly, coupled with ever-changing consumer behaviours. Rather than view digital transformation as an end goal, organisations will have to consider it a constant process that will enable them to adapt, evolve, and drive forward change within their field. Ideally, it is the state of flow that all businesses should be striving for.
Get in touch to find out how Digital Transformation can revolutionise your business.
