Businesses should tackle data management
Investing in master data management makes sense even in a tough economy, argues Gartner.
Businesses should be increasing their investment in data management, in order to create consistent and high-quality master data sets, according to industry analysts.
Gartner, the IT research firm, believes that spending on master data management (MDM) grew 14 per cent to US$1.5bn this year, despite the tough economy.
Investing in data management will become more important still as the economy recovers, the analysts suggest. Customers will demand better service from businesses, and companies will need to improve data quality for compliance, reporting and risk management.
The firm expects spending on master data management to continue to expand, with a compound annual growth rate of 18 per cent between now and 2014. Growth is being driven both by offerings from specialist vendors and the large, enterprise software companies, along with increasing demands for data management from specialist business functions such as human resources and the supply chain.
But a growing market for MDM software will not, in itself, solve all business issues around data quality, Gartner cautioned. Businesses may lack the skills to deploy in-house MDM tools, especially for niche applications. Companies should look instead to use cloud-based data management services, in order to bridge the skills gap. Subscription or cloud-based models will also be more acceptable where data management projects are being carried out for just one area of the business.
And data management also needs to be tackled as a business project; if it is handled by IT alone, companies will not see its full value. "The business needs to take responsibility and be accountable for master data management," warned Gartner research vice president, John Radcliffe. "With MDM, CIOs can create a unified view of existing data leading to greater enterprise agility and ultimately improved profitability."
Previous industry research has shown that most business data is still not good enough to drive quality decision making.
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