Opéra’s specialization is based on data

Our teams support our clients on processes and tools to increase their efficiency through the use of data.

The « data specialization » integrates several expertises from the data audit to the integration of an operational solution.

Your SI challenges around DATA

  • To be attentive to business needs and changes.
  • Leading the transformation in an Agile way.
  • Do not destabilize the existing.
  • Benefit from scalable and flexible systems.
  • Manage and analyze high volume data.
  • Ensure data storage and governance.
  • To be compliant with DSI processes.
  • React in real time.
  • Explore data in ergonomic form (dashboards).
  • To be compliant with the regulations (in particular RGPD).
  • Have easy access to all types of data.
  • Talking about a common language of company data: simultaneous business and IT vision of the data dictionary
  • Have a collaborative orientation (connect people, share their assumptions, synchronize their actions)
  • Ensure freshness and quality of data
  • Controlling decision-making costs

Our business intelligence offers

Data mining. What is the actual activity? What areas of study should be focused on?

Activity supervision. What is the history? What are the trends?

Fraud detection. What volume is involved?  What countermeasures to expect?

Performance indicators. Where are we going? By what deadline?

Marketing reports. How to adapt the campaigns? What results were obtained?

Real-time supervision. Should we react immediately to an alert?

Real-time customization. Which interface is adapted to each user?

Perpetual study of past events. What conclusions can be drawn from historical / recent activity?

Identification of profiles by segmentation. What are the interests of this profile? Which audience should I focus on for my activity?

Development of predictive models. What is the probability of a purchase? (e-commerce) of an accident? (insurance) of a dispute? (bank)

Our missions in Business intelligence

Audit of customer needs: understanding concerns and objectives

State of the art of available data: mapping, quality assessment and reliability

Preparation and structuring of data: choice of storage, modeling, performance

Data content exploration: implementation of analysis algorithms and valorization (by data scientists)

Dissemination of results

Industrialization: implementation of operational architecture, training in the autonomous use of the solution

The organization’s vision – a compromise between users and IT

The trade-off is user agility and IT control

The solution vision – business requirements

ergonomics-performance-accessibility-attractiverses

Ergonomics –> dashboards respect the principles of usability

          • Information limited to the essential
          • Legible and understandable presentation for all users
          • Ease of use
          • Efficiency of use

Accessibility –> multi-channel

          • Integration into the company portal
          • Widget integration in management applications
          • Diversification of terminals: desktop, mobile, tablets
          • Massive distribution in various formats (Excel, PDF, etc.)
          • Email alerts

Performance –> at the service of the user

          • Optimization of feed requests
          • Constantly questioning the data model
          • Respect of tuning recommendations on the DBMS side, table indexing, etc.

Attractiveness –> vectors for a better flow of information

          • An irreproachable data quality (relevance, reliability, freshness,…)
          • Intuitive use (direct access to the desired data, possibility to navigate, driller…)
          • A careful design (choice of colors, use of images stronger than words)
          • A choice of diagram always adapted to the information represented
          • A permanent fight against redundant information on the screen

The solution – performance vision

BI SOLUTIONS must be FAST, FLEXIBLE, EFFICIENT AND LOW COST

Despite the increase in data and complexity, business intelligence solutions must be simpler, respond immediately and everywhere to new business issues.

Lean approach

  • Realize projects in several weeks instead of several months and with minimal investments (reduce Time to Market)
  • Remain flexible with changes
  • Focus on needs that are potential sources of profit
  • Develop data management with solutions based on light, flexible, intuitive architectures that can be easily integrated into existing information systems (full web), that communicate with each other, etc. with or without Big Data

Our skills / certifications in Business Intelligence