Companies will spend an average of $7.4M on data-related initiatives over the next twelve months , with enterprises investing $13.8M, and small & medium businesses (SMBs) investing $1.6M.
80% of enterprises and 63% of small & medium businesses (SMBs) already have deployed or are planning to deploy big data projects in the next twelve months.
83% of organizations are prioritizing structured data initiatives as critical or high priority in 2015, and 36% planning to increase their budgets for data-driven initiatives in 2015.
These and other key take-aways are from the recent IDG Enterprise study, 2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments. You can find the slides for the presentation here. The methodology is based on interviews with 1,139 IT leaders from nine industries with high tech (16%), government (12%), financial services (11%) and manufacturing (9%) being the top four industries surveyed. Please see the first two pages of the study for more details regarding the methodology.
Additional take-aways include the following:
- – 80% of enterprises surveyed have data-driven and big data projects in implementing or planning stages today versus 63% of SMBs. 37% of enterprises have deployed data-driven projects in the last year, and 18% are in the process of implementing or piloting projects as of today.
- – Improving the quality of decision making (61%), improving planning and forecasting (57%) and increasing the speed of decision making (51%) are the three most common business goals and objectives driving data-driven initiatives in organizations today. The following graphic compares which business initiatives are driving big data investment and the positive impact of big data on each.
- – 36% of enterprises expect their IT budget allocations for data-driven initiatives to increase in 2015, 41% anticipate budget levels will remain at current levels and 21% aren’t sure. Only 3% say data-driven and big data-related project funding will decrease.
- – Data analytics continues to accelerate as the most preferred solution for gaining greater business insight and value from data, with this category increasing in importance 55% from 2014 survey results. In enterprises, data analytics (65%), visual dashboards (47%), data mining (43%), data warehousing (40%) and data quality (39%) are the five most preferred solutions. In my discussions with CIOs in financial services and manufacturing companies, the shift away from pre-built dashboards with common metrics and key performance indicators (KPIs) to the flexibility of defining their own data models in metrics is the future. Dashboards in financial institutions need to have the flexibility of quickly integrating entire new metrics and KPIs as their business models change. For manufacturers, the need for interpreting shop floor data to financial results is what’s driving data analysis and dashboards in the many manufacturing industries adopting analytics today.
- – The number of enterprises who have deployed/implemented data-driven projects increased 125% in the last year, with 42% still planning data implementations as of today. The following graphic from the study illustrates a comparison of 2014 and 2015 plans for considering, planning and implementing data-driven projects.
- – Enterprises most often face limited budget constraints (45%), legacy system issues (41%) and limited availability of skilled employees to analyze data (40%) as their biggest challenges in getting big data initiatives up and running. The following graphic compares challenges of enterprises relative to SMBs.
- – Security continues to be a major concern of enterprises implementing data-driven initiatives including those encompassing big data-related projects. 76% of enterprises are restricting access to sensitive data to limited individuals, up from 52% in 2014. From discussions with CIOs, the focus on enhanced role-based authentication and access is now commonplace in their organizations. Encrypting sensitive data (53%), storing all sensitive data on premise (40%) and storing sensitive data across multiple silos rather than centralize (23%) are also becoming commonplace. The following graphic compares how enterprises are restricting access to safeguard sensitive data.
- – In 2015 enterprises are looking to hire more business analysts (23%), data architects (23%), data analysts (20%), data visualizers (19%) and database programmers (18%). The following graphic compares enterprise employee’s skill sets in-house relative to 2015 hiring plans.
- – When evaluating analytics and data solution vendors, integration into existing infrastructure (51%), ability to meet security requirements (40%), ease of use (35%), appropriate level of scalability (35%) and support and services (34%) are the five most important criteria enterprises are using today. The following graphic compares the top nine by enterprises and SMBs.
- – The most common sources of data in enterprises adopting and implementing big data and data-driven projects include customer databases (63%), e-mail (61%), transactional data (53%), worksheets (51%) and MS-Word documents (48%).
- – CIOs (52%), CEOs (43%) and IT/networking staff (37%) are the top decision makers on which data-driven projects and initiatives are pursued in enterprises. In SMBs, CIOs (30%), CEOs (14%), IT steering committee (8%) and CTO/IT Architect (8%) are the top data driven and big data project decision makers.
This article was written by Louis Columbus from Forbes and was legally licensed through the NewsCred publisher network.