The Big Data age has arrived but, contrary to popular belief, it’s not just for large companies: advancements in technology and falling costs of hardware allows small and medium-sized businesses to exploit Big Data. But why would you bother? Is your data big enough? And how do you get started?
What exactly is Big Data?
Big Data refers to data volumes that are too large, too complex, too variable or too unstructured to be analysed using traditional data-processing methods. The digital age has led to an explosion of data and it's now regarded as an incredibly important business asset.
Why use it?
By using Big Data, you can uncover insights into your customers, your products and your market. Several areas that are ideal for implementing Big Data analytics include sales, marketing, R&D, production and administration. These insights can be used to make more informed decisions, ultimately leading to efficiencies, increased profits, new products and services, and happy customers. By using your data assets, and the insights gained from them, you can make better informed and faster decisions, helping increase management and leadership efficiencies.
How can I get going?
Step 1: What can you do with your data? What’s your goal?
Before you get going with Big Data, you need to figure out what you are trying to achieve. Too often companies start data analytics without having a clear goal in mind and they end up trying to find out everything in one go. Identify one key goal: Do you want to get a better understanding of what the experience is like for your customers? Perhaps you’d like to know more about who your customers are and why they choose to buy from you? You can glean insights on just about every element of your business if you have the right data, so start gathering it today to ensure your success tomorrow.
Consumers visit websites for different reasons, but around 96% of them leave without actually buying or booking anything. myThings uses data-driven dynamic banners with personalised product recommendations to rekindle the interest of these anonymous users, increasing click and conversion rates by up to 150%. myThings’ goal is clear; increase sales conversion.
Step 2: Find your data
Part of the data auditing process requires an understanding of where the data is. To get a full picture of what’s going on, you will need to be able to access your data from a central location. Smaller businesses tend to have lots of excel spreadsheets throughout the organisation in varying formats and some key staff may hold it in their heads. Most people don’t understand the value of the data within these repositories. It’s important to create a data culture within your business to ensure you get the right data to be able to gain insights that will have a meaningful impact on your business.
FMCG (fast moving consumer goods) brands generate a huge amount of data each day, from sales figures to supply chain information. Atheon Analytics collects billions of rows of data automatically from grocery retailers and visualises it in interactive dashboards. This allows the brands to use the data to analyse sales, promotions and stock availability to understand the pricing and promotions that will work the best. It allows even smaller FMCG brands to gain insights that were previously the reserve of only the largest supermarket chains.
Step 3: Tidy as you go
As data analytics is about gaining Business Intelligence (BI), it is essential to not simply capture your data, but to ensure that it is easily accessible. As an increasingly important business asset, you need to make sure the data is of the best quality possible before using it for analysis.
You need to audit your data and improve its accuracy as well as educating all employees so they know what you are trying to achieve, and they understand the value of saving data in a standardised format. It makes for better analysis.
Step 4: Select the right tools for the job
Once you have established what you want to do with the data you have, you need to find the right tools for the job. The tools needed will vary drastically between businesses depending on whether the business model already focusses on data analytics, or if a business is analysing data to improve its sales process or customer service. The tools needed will also depend on how much data you currently have, how much you expect to have in the future and the speed at which you need to analyse data to maintain a competitive advantage.
But how do you decide what tool to use? SQL or NoSQL databases? Columnar or row-stores? Open source or proprietary? Cloud or on-premise? Reports or visualisations? BI and reporting tools? There are so many options it may seem bewildering.
The best way to find the tool that suits you is to shortlist a few and then try before you buy; most vendors allow you to sign up for a free trial or community edition, and built-in connectors should allow them to hook together simply. The key thing to bear in mind is whether your chosen solution will scale. While it may work for your business now, will it work for your business in six months? And in five years?
Big Data for big success
Big Data can help inform your company’s strategy, save precious time in decision-making and help you make more accurate decisions. There is no one-size fits all solution, but if you make sure you have a clear objective, have a team that is committed to the project, know where your data is, keep it tidy and use the right tools, you’ll reap the benefits of the Big Data age.