Data Analytics Virtual Assistant

Strategic consulting

Strategic consulting helps companies optimize business processes to align them with customer needs. Our consultants will help you establish strategic and business planning in various areas, from risk management to human resources, from administration to logistics, in order to make your company’s activity more efficient and adopt the best techniques and technologies necessary to ensure an evolved control of your company.

Data Innovation Program

A data-driven approach protects your company from decisions that don’t fit your business plan. Our consultants help you design the infrastructure, increase analytical competence, and organize the people who will be responsible for sharing information within the organization. A three-step program for a data-driven corporate culture and excellent results.

Visual renewal

Good analysis certainly depends on good data, but it’s also up to the visual aspect and design of the dashboard to provide clear information to your audience. Having advanced technical knowledge doesn’t always mean being able to effectively communicate your ideas to others.

Many dashboards we see are functional, but they lack the design elements that help the information to be easily understood and make it appealing to the viewer. Nothing a makeover can’t fix. A makeover gives us the opportunity to take into account data and client needs, as well as allowing us to customize the report with logos, corporate colors, iconography, and style.

Process automation

Automating repetitive, manual processes that do not add value increases employee engagement and task accuracy, and reduces errors. Our solution starts with an assessment of the company’s state of affairs to graft automation into processes in order to simplify workflows and maximize performance.

Analytics on demand

Our service includes several packages of fixed days per month for maintenance and development to accelerate the return on your investment and consolidate an ideal culture towards transformation into a data-driven company. You will get a virtual assistant data analyst for your project.

Data Gathering

The primordial phase of the data analysis process cannot ignore a careful and clear definition of what the problem, the need, the necessity that the analysis itself has as its objective is. Identifying the desiderata and the value that the analysis must bring to the business helps guide the subsequent phases that are downstream.

Data Collection

Based on the output of the first phase of requirement analysis, we move on to collecting the necessary data to satisfy the final needs, the behaviors that we want to evaluate and the aspects that need to be measured.

Data Processing and Organizing

After collecting data from sources, they must be processed and organized appropriately to be used in the analysis phase. At this point, measures such as referential integrity checks or data conversion into a format useful for subsequent processing are applied.

Data Cleansing

Once organized and processed, data may be incomplete, contain duplicates or errors. To ensure that the results generated by the analysis being prepared are consistent and reliable, it is important to plan Data Cleansing initiatives that are able to provide an adequate level of Data Quality.

Analysis / Communication

Cleaned and organized, the data is ready for the actual analysis phase. Depending on the techniques chosen, this step can be approached in profoundly different ways. However, what these different ways of tackling the problem have in common is communication towards stakeholders who are interested in or have directly commissioned the data analysis in question: the information can be reported in different formats to meet the initial requirements. To do this, different data visualization methodologies are often applied in order to guide the communication of the key messages contained in the analyzed information.

Marketing

Data mining technologies and algorithms are now a consolidated approach in increasingly targeted targeting of customers to engage with ad-hoc advertising and advertising campaigns. Among the many, Coca Cola has undertaken heavy analytics initiatives to be able to support its operations thanks to its customers’ data.

Manufacturing

Advanced analytics using machine learning and artificial intelligence techniques are fueling the transition to Industry 4.0 where high connectivity between machines and components can help optimize production processes and apply predictive maintenance initiatives where production blocks and failures can be avoided (typically they also require prescriptive and automated components to replace human intervention in certain situations). Bayer and Rold are Italian examples of excellence in this context.

Finance

This area lends itself to various applications, such as the use of descriptive BI to provide meaningful summary indications on the main trends to compare the performance of different financial instruments, up to more advanced techniques to predict market trends or identify fraud in advance and act accordingly.

Logistics

Analytics also support particularly effectively the operations of optimizing the storage of goods between central distribution centers and smaller ones located throughout the territory to reduce shipping costs. Applying association algorithms between products to understand which less popular ones are generally bought by the more widespread ones, allows warehouses to be better stocked, consistently with the policy of saving costs and streamlining shipping times.

Cyber ​​Security

Advanced statistical analysis of data from your company network and monitoring devices in communication with the outside are fundamental steps for identifying anomalies and predicting potential intrusions.

Asset Management

Business Intelligence products, especially visual, summary and geospatial, allow you to monitor the status and KPIs associated with different assets (bridges, pipelines, tracks, for example) to organize maintenance cycles and intervention areas.