Ready to chat data? That's what we're here for
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.
The amount of data generated, consumed and handled on a day-to-day basis is bigger than ever before. ‘Big data’ has transformed business practices, to the point where a company’s use and collection of data can be integral to its success.
More data of course means more processing, which can significantly add to your company’s workload. That’s where data automation comes in.
With a reliable automation system, mundane data handling tasks can run effortlessly in the background, freeing up your workforce to work on other things and increasing overall results.
Data automation can be achieved using business applications such as Excel and Power BI. It is implemented to take over general ongoing data-related tasks that would usually require a lot of time and energy.
Types of data automation include:
Data automation can be used in various departments within businesses from a variety of sectors. Some of the most common can include:
Perhaps least surprisingly, data automation saves a tremendous amount of time. Not only can it take care of multiple processes at once, but it also saves staff from having to perform arduous, time-consuming tasks, such as data collection, filing, analysing and processing. This frees up your workforce for more important projects, thus boosting overall productivity in other parts of the business.
Data automation also leads to increased visibility. Imagine clusters of filing cabinets in different places, all stuffed full of important data that was a chore to sift through. Thanks to cloud-based storage, data can be made available to anybody who needs it from wherever they are. Saving precious time and streamlining workflows.
Many manually processed documents like invoices will pass through several hands before finally being approved and paid. In fact, research firm Gartner found that the cost of processing invoices in the UK was on average anywhere between £4 and £25, with some businesses even spending £50 per invoice.
Meanwhile, data capture automation has been found to cost up to 20 times less than manual data capture. Providing a seriously lucrative opportunity for businesses to shave pounds off their processing costs (and take pressure off finance teams!).
Many accounts-payable departments have numerous hidden costs and expenses. Not to mention that manually storing data requires added labour, organisation and office space costs. Imagine how much you could save…just by automating your data processes.
Because automated data systems can process many datasets or documents per minute. This helps to increase output massively, leading to faster turnaround times, more relaxed staff and inevitably, happier clients.
As well as encouraging more satisfied staff (who will surely appreciate not having to spend endless hours on mundane data entry tasks), it also frees up space in the business for growth, creativity and innovation. It can be said that a company is only as good as its data. Continuously monitoring, refining and modifying one’s business strategy requires access to accurate and relevant data, all of which will contribute to sustained business success.
Data automation doesn’t just make it easy to collect and access data; it also provides extra security too. Most automated data management systems continuously create back-ups of your data in the cloud, so your data is always available and always preserved.
As mentioned earlier, data capture and processing can be difficult, time-consuming tasks – ones that very few people can do for hours on end without making a mistake.
Natural human error and eventual fatigue will undoubtedly lead to errors somewhere along the line. Meaning lost time and more costs for your business to put right. Remembering the 1-10-100 rule, a company could spare far more money by ensuring they have all their data processes properly automated, in order to prevent as many errors as possible and be able to detect and address issues quickly when they do come up.
This will in turn lead to a smoother, more improved service for your clients and set your company apart from its competitors.
Bespoke can help you find an effortless automated data solution that fits seamlessly into your business.
Get in touch with our team to discuss your business needs. Or take a look at our range of solutions to see what we can do for you.
