According to a new study - titled "Data Modelling and Collaboration: Insights for Business and Data Professionals" - released today by Embarcadero Technologies, data professionals have little confidence in the way business stakeholders within their organisations use corporate data when making important business decisions. The research finds three out of four (75%) data and development professionals suspect business stakeholders misuse data when making business decisions, while 81% believe the data used is misinterpreted.
The Embarcadero study conducted by Dimensional Research shows:
* Only 13% of data professionals believe the right data is always being used, while just 9% say the data is being interpreted correctly by business stakeholders.
* Business stakeholders in large companies are more likely to make mistakes with data, with organisations of 5 000+ employees ranking the highest for misusing and misinterpreting data.
* "Data silos" - databases or data sources that are not integrated for use across the organisations - are more common than IT executives realise; 44% of individual contributors versus only 23% of executives say their organisations have many silos.
Organisational issues contribute to data challenges
According to the research, 100% of those executives surveyed agree that it is important for data and development teams to communicate well, while only 25% believe there is actually good communication between the teams within their organisations.
* 85% of executives whose IT organizations use new data platforms (e.g., cloud, graph, columnar, and Hadoop databases) say that communication between data and development teams is very important.
* Only 24% of developers think their data team is fast and responsive.
* Less than half of data teams (45%) say they are included at the beginning of a project, while 25% say they don't find out about a project until it's too late for them to do their best work.
Data models are valued but not effectively used
Survey results indicate that developers overwhelmingly believe in the value of data models, and the formalisation and documentation of existing processes and events that occur during application software design and development. But only 20% say IT leadership fully understands that value.
* 87% use data models but only 18% have a data modelling team responsible for them.
* 95% of developers say the use of good data models increases the quality of an application.
* 95% of data stakeholders say application and data quality would improve if developers understood data modelling better.
Top three challenges of data modelling
The research reveals that almost half (49%) of developers and data professionals include input from business stakeholders when developing new data models. But 96% of developers report they have challenges with data models, with the top three being:
* "Moving data between platforms or formats": 52%;
* "Business stakeholders and IT using different terminology for data": 43%; and
* "Business stakeholders not getting full value from the data available": 43%.
Agile data modelling fosters better data and collaboration
According to survey results, just 16% of participants have fully embraced an agile development methodology; however 95% of participants see value in agile data modelling.
* More than half of the participants rank "increased data accuracy and integrity" (52%) and "better collaboration between data modeller and development teams" (51%) as the top two benefits of agile development.
* Only 8% say those responsible for data models are not included in their agile process.
"New technologies for capturing, storing, and analysing data are revolutionising the way business decisions are made," says Michael Swindell, Senior Vice President of Products at Embarcadero Technologies. "As corporate data becomes more of a strategic asset that drives business decisions, the consequences of relying on the wrong data can be disastrous for the enterprise. New agile and team enabled data modelling tools like ER/Studio and ER/Studio Team Server are helping organisations to embrace data modelling in tandem with collaborative, agile workflows to ensure data quality and integrity, and to establish the foundation for a business-driven data architecture."