Today’s finance and accounting professionals face ever-growing challenges when it comes to data. The simplest analyses can be complicated by the wrong data or bad data and too much data can even be a problem. Effectively sourcing, managing, and using data are key skills.
A recent Accenture study showed that 79% of large company executives think that companies that don’t manage big data properly will get left behind. But, data alone is not what businesses are after. They’re after what they think data can do for them. They’re really after the insights they can glean from data that will help them improve their decision making and the actions they take to move their businesses forward.
The explosion in computing and data processing power has led to an exponential increase in data available to business. Paradoxically, this has led to business leaders becoming more uncertain about what to do with this data. Hence, business is scrambling to put the appropriate “analytics” capability in place. This generates a lot of friction and tension because business leaders and managers, who have been brought up in a very different world, have to scramble to learn new languages and redress their relationship with data.
According to a recent survey by Prophix and FP&A trends, 88% of companies claim they have data quality issues. The aim of this blog is to sketch the main steps that you can take to ensure that your company belongs to the remaining 12%.
‘Getting the right data to the right people at the right place and time’ is the essence of the whole concept of data management. You can plan big steps for the long-term while making small steps to improve the situation in the short-term perspective.
This article explores the attributes of Big Data and considers whether having more data is always good. First, let's get back to the basics. What is Big Data? Put simply, big data refers to a vast variety of data with which an organisation can engage. The aim is to use big data to improve business performance. This is applicable to profit and non-profit organizations, financial and operational measures.