Less poor data is essential
Data quality is about making sure that data are accurate and coherent.
What type of organization, big or small, can say that they’re not concerned by data quality ? None, of course.
Many different types of data are collected (for research, transactions, customer or administrative care, demographics, social media activity, surveys, basically all informations aimed at statistics…).
Whether to properly manage the ever-growing amount of various data or to build towards customer satisfaction or to meet internal control requests, data must be consistent. Once an organization commits to such rigorous but necessary fulfilment, the path is made clear for every user at every level of the data “chain”.
But what is good data quality ?
All the information the user needs to work is provided by the Business Intelligence tools and data warehouses where the data is stored. This information is the result of an aggregation of data made in accordance with predefined rules inside the organization. To provide good quality data to the user implies good quality data taken individually, and coherent data aggregation.
Data quality discovery and monitoring are important aspects of the technology used to reach good data quality (aka data profiling).
- Data quality concerns and has an impact on every level of an organization.
- Financially : costs caused by « bad » data quality are important.
- A good data quality has very important hidden benefits.
The significant loss of time and turnover to « bad data » creates a crucial need for data governance (as opposed to the occasional data cleansing which only leads to short-term profit). Other direct/indirect costs of bad data quality can also be customer loss and damaged company image. Decision making, marketing, selling, logistics… each of these pivotal functions inside the organization will greatly benefit from a good data quality mindset.
Improvement of revenue (ROI), reduction of risk, increased efficiency of the workers… It speaks to every business manager, doesn’t it ?
In a previous post we already discussed how poor data is a damaging factor for businesses : what good are bad or incomplete contact data; what’s the use of incoherent or inaccurate data in a marketing concept; how can any department really be efficient if their initial material (the data) is obsolete or even partly unusable ?
Since we established that data is everywhere and essential to organizations, and foreseen that with current technologies the situation is going to keep evolving exponentially (big data of course comes to mind), what are you going to do about it ?
First analyze your data needs according to your business requirements; then decide which data is crucial to clean/govern/integrate (in other words, keep your data in check); finally choose a data quality strategy and partner to accompany you in this daunting yet absolutely necessary task for the sake of your business.
You will quickly see that a good data management system is the answer to all your problems. And we dare to claim that it will even highlight new asset possibilities for your business.