Data quality traps: Easy to fall into, but hard to get out of
Big data adoption is picking up, with nearly half of surveyed businesses saying they are developing plans to use it and 28 percent reporting they have already tested projects or have one underway, according to a study by the University of Oxford Said Business School and the IBM Institute for Business Value.
Big data shows big promise
That's because it enables firms to harness content generated on information management systems, social media sites, point-of-sale terminals and other real-time data and turn it into information that could lead to valuable insights, as business news network Bdaily explains.
"The adoption of big data initiatives is a process which relies on the availability of the data itself, but also on the technologies and skills to utilize it to create value and for competitive advantage," said Dr. Janet Smart, fellow in management at Said Business School and co-author of the report, as quoted by the source.
Dave Kay, vice president of Sales for IBM United Kingdom and Ireland, explained that tools and specialists are needed to account for variability in the data they collect, whether it's from internal or external sources, the media outlet adds. Rushing into a plan without acquiring the necessary implements can keep companies from developing the competitive advantages they seek.
Big data can lead to big mistakes and lost credibilityIf companies don't invest in adequate verification tools, they could end up with poor data quality. Unfortunately, most companies don't realize there are informational inaccuracies until it's too late. Even one mistake can cost businesses significantly when it comes to their reputations, Smart Data Collective points out, adding that a single slip up can challenge reliability and lead to doubt in the long run.
Correcting those incidents can only occur when organizations admit what went wrong, address the fears that were born out of the mistake and realign data quality standards with those of end users.
Building the systems doesn't mean insight will come
Similarly, problems can arise if businesses launch into big data strategies with false hopes. CMS Wire points out that developing the systems for collecting data does not necessarily mean companies can use content to gain helpful information, let alone valuable insight. Those advantages can only be achieved when enterprises filter content sets and have the data quality tools in place to make them interpretable, relevant and novel.
Big data shows big promise
That's because it enables firms to harness content generated on information management systems, social media sites, point-of-sale terminals and other real-time data and turn it into information that could lead to valuable insights, as business news network Bdaily explains.
"The adoption of big data initiatives is a process which relies on the availability of the data itself, but also on the technologies and skills to utilize it to create value and for competitive advantage," said Dr. Janet Smart, fellow in management at Said Business School and co-author of the report, as quoted by the source.
Dave Kay, vice president of Sales for IBM United Kingdom and Ireland, explained that tools and specialists are needed to account for variability in the data they collect, whether it's from internal or external sources, the media outlet adds. Rushing into a plan without acquiring the necessary implements can keep companies from developing the competitive advantages they seek.
Big data can lead to big mistakes and lost credibilityIf companies don't invest in adequate verification tools, they could end up with poor data quality. Unfortunately, most companies don't realize there are informational inaccuracies until it's too late. Even one mistake can cost businesses significantly when it comes to their reputations, Smart Data Collective points out, adding that a single slip up can challenge reliability and lead to doubt in the long run.
Correcting those incidents can only occur when organizations admit what went wrong, address the fears that were born out of the mistake and realign data quality standards with those of end users.
Building the systems doesn't mean insight will come
Similarly, problems can arise if businesses launch into big data strategies with false hopes. CMS Wire points out that developing the systems for collecting data does not necessarily mean companies can use content to gain helpful information, let alone valuable insight. Those advantages can only be achieved when enterprises filter content sets and have the data quality tools in place to make them interpretable, relevant and novel.