A data lake, in essence, is a repository that can store an infinite amount of both structured and unstructured data for later use. In a previous article, we have briefly explained a few noticeable differences between data lakes and data warehouses. Each type of data repository serves a unique purpose. Therefore, instead of replacing one with another, they can be used supplementarily.
Recent TRG blog posts
In previous blog posts, we have discussed about why workflow automation software is a worthwhile investment as it frees up human resources, increases efficiency, reduces errors in both information gathering and overall processes, and reduces your overall costs.
As we have explained in earlier blog posts, proper document management is a challenging but worthwhile practice. However, if you have decided to invest in a document management system (DMS), a whole new problem arises – Which one do you choose and what does such a system even need?
Many businesses today are still relying on paper registers, massive spreadsheets and human resources to manage a lot of workflows in their business. Operations such as inventory reporting, sales approval and customer experiences that are managed manually will often result in many bottlenecks as operations become backlogged because of the sheer amount of data that needs to be catalogued and processes that need to be done. As a result of this, data is often lost or incomplete, and productivity and efficiency is reduced.
Businesses across all industries have two things in common: they utilise documents and they create a lot of them. Documents are used for everything from sales reports to product development and end up being stored in all sorts of places, both digitally and physically.
Document management is often an overlooked practice in your business, but did you know that according to research your employees can spend up to 20% of their time at work searching for information about the task they are currently doing?
As planning, budgeting and forecasting become indispensable strategic contributors, finance executives begin to realise the need to transform their rigid yearly financial planning by adopting more advanced (both on-premise and cloud-based) analytical tools. 71 per cent of organisations surveyed by FSN in 2017 has been able to reforecast more than twice a year, up from 56 per cent in the previous year, although the forecasting accuracy is still fairly low.
Analytics and Business Intelligence (BI) software is increasingly becoming indispensable to organisations seeking to be more data-driven. Accordingly, software vendors are working hard to ensure their products can provide actionable insights from analytics, communicate the results, and support the internal communication and collaboration between functions when needed.
The amount of data generated throughout today’s manufacturing process – from product development to production and post-sales support – is astonishing. That said, the capabilities to utilise such data volume is not yet catching up. For instance, an oil-exploration company was able to collect more than 30,000 pieces of data from one single drilling rig. Most of that data, however, was wasted.