DATA & ANALYTICS
SAP Analytics Cloud
Boost your analytics with SAP Analytics Cloud, the ultimate SaaS Analytics solution (100% cloud based) so that business users can perform conventional analyses on their own without IT support and obtain insightful information, discover influencers, odd values and make predictions.
In 2016, SEIDOR became pioneers in the implementation of the first versions of SAC, and, over the past five years, our team has completed more than 80 projects. Multiple deployments on SAP and non-SAP data sources.
Eduardo Gual
CIO
ERCROS, a pioneer in the deployment of SAP analytical solutions, has deployed hundreds of business indicators and detailed reporting over the last two years for the commercial, logistics, transport and purchasing areas with SAP Analytics Cloud.
Users familiar with the business context need to be able to perform their analysis autonomously without requiring IT support
Need for automatic learning and increased analytics to bring value and ideas and facilitate decisions through guided analysis.
Start a planning process from the results of a history-based algorithm without the need to hire data science specialists
Manual mining of information is necessary to ensure that we are not ignoring any kind of insightful information that would change the direction of decision-making
FEATURES
Automatic search for insightful information (Search to insight)
Search using natural language to obtain displays and graphs and, thus, be able to answer questions instantly.
Smart Insights
Automatic learning technology allows you to save time and focus on more valuable activities
Smart discovery
Lists data to understand how factors influence commercial, supply, production or cost control processes.
Smart simulation
Automatically generate predictive models that will allow you to simulate how changing certain variables or parameters influences KPI's.
Benefits
Real-time analysis
Direct connection to the transactional systems without latency and automatic disclosure of information, allowing key people to spend their time making decisions rather than mining information.
Increased analytics
Use of predictive techniques without the need for technical skills to obtain key information that assesses all relationships between products, customers, temporality, suppliers, cost centres, etc. and improve processes.
Collaborative planning
As this is a section with its own entity, while analysing the data, we can make flexible and collaborative plans and compare them with the real data