Data quality: Whose job is it? -

Data quality: Whose job is it? –

Data quality: Whose job is it? –

A recent survey suggests a significant disconnect in many organizations between the people creating data and those managing it.  

The IT department is usually held responsible for maintaining quality data, but those entering the data are not. “Data quality responsibility, for the most part, is not assigned to those directly engaged in its capture,” according to a survey by 451 Research on enterprise data quality.

When perceptions of the two groups -- those “accountable” and those “responsible” -- are misaligned, data quality suffers, the report said, and IT departments must employ multiple cleansing technologies to compensate, even as the volume of data grows.

Clean data is important for business. Sixty-five percent of respondents said that nearly half of business value can be lost to poor data quality, and 29 percent thought the consequences would be were worse.

Bad data comes from many sources, but the biggest cause is improper data entry by employees. Data migration or conversion projects come in second, followed by mixed entries by multiple users, changes to source systems, systems errors, data entry by customers and external data.

Read Also:
Kinetica Aims to be The Data Science Accelerator with its GPU-Accelerated Database

Problems caused by poor data quality are numerous. It forces staff to spend extra time reconciling data, contributes to extra costs, lost revenue delays in deploying a new systems and bad decision making.

Despite recognition of the problem, respondents’ confidence in their organization’s data quality management (DQM) practices is not high. Less than half (40 percent) of respondents to the survey were very confident that all the data sources required for their purposes had been aggregated prior to cleansing.

 



Chief Analytics Officer Spring 2017

2
May
2017
Chief Analytics Officer Spring 2017

15% off with code MP15

Read Also:
State Street Tests a 'Rosetta Stone' for Bank Databases

Big Data and Analytics for Healthcare Philadelphia

17
May
2017
Big Data and Analytics for Healthcare Philadelphia

$200 off with code DATA200

Read Also:
Big Data No Longer a Big Problem

SMX London

23
May
2017
SMX London

10% off with code 7WDATASMX

Read Also:
Kinetica Aims to be The Data Science Accelerator with its GPU-Accelerated Database
Read Also:
Five Best Practices for Building a Data Warehouse

Data Science Congress 2017

5
Jun
2017
Data Science Congress 2017

20% off with code 7wdata_DSC2017

Read Also:
2016: The year AI got creative

AI Paris

6
Jun
2017
AI Paris

20% off with code AIP17-7WDATA-20

Read Also:
Big Data and IT Asset Management: A marriage made in heaven or hell?

Leave a Reply

Your email address will not be published. Required fields are marked *