A report on the future adoption of cloud analytics from Informatica and conducted by analysts IDG Research finds that cloud analytics adoption has reached a tipping point with 68% of respondents saying that over the next 12 months they will be investigating, analysing or actively planning to deploy cloud analytics solutions.
The businesses surveyed with cloud analytic projects in the works or on their radar are it seems investing heavily, with on average, 17 analytics projects underway or in planning in the next 12 months. Of those projects, 46% will involve the use of cloud analytics solutions.
Additionally, 74% said they expect to adopt a hybrid or cloud-only approach to analytics over the next three years. While the take-up of cloud analytics is currently low with just 15% deploying one or more cloud analytics solutions, those who have adopted cloud analytics already are seeing ‘significant business value.’ Respondents with deployed cloud analytics solutions cite the advantages of lower upfront costs (60%) over on-premise solutions, as well as greater agility and faster time to market (61%), more rapid and cost-effective scaling for larger data sets (60 %) and self-service capabilities for non-technical users (51%).
According to the survey the movement to cloud analytics adoption is being driven primarily by escalating end-user requirements for improved analytics, including improved quality and consistency of data across systems (81%), improved ways to visually explore data (70%) and real-time data aggregation and analysis (71%).
Adoption is also being driven by the need to access an expanding range of data sources, both cloud and on-premise, respondents cited the need to analyse data from on-premise applications (55%), on-premise data warehouses (55%), cloud data warehouses (49%) and SaaS applications (44%). Support for big data sources is another specific demand (67%).
When it comes to purchasing cloud analytics the survey was able to offer a number of helpful evaluation criteria with the top five being; robustness of data security framework (81% rating this as critical or very important), ease of use (78%), ease of on-going administration (77 %), ability to integrate on-premise and cloud data (78%), and ability to reconcile/cleanse data (74%). These were followed closely by the availability of implementation resources and speed of implementation.