Data Analytics
How analytics are evolving and the importance of metrics
“Measure what can be measured, and make measurable what cannot be measured”
Galileo Galilei
You can’t manage (but most of all, improve) what you can’t measure
And when it’s about measuring, the modern scientific tools are the ones coming from Business Intelligence (BI), Business Analytics e Big Data Analytics softwares.
Business Intelligence
BI tools, generally used for query activities, can acquire and elaborate a wide series of data, providing several benefits in terms of business strategy.
More in specific, they can:
- boost and improve decision-making processes;
- increase operational efficiency;
- find new revenue opportunities;
- identify new market trends;
- create reports based on KPI indicators;
- define new business opportunities.
Business Analytics
Business Analytics tools can offer a corporate overview, providing precious information such as business operations or customer conversion rate.
These tools can:
- help identifying weaknesses;
- find problem areas and fix them;
- inform decision makers about unexpected events;
- forecast future results depending on the business decisions.
The combination of these tools allows organizations to gather all necessary information in order to achieve the business goals, keep the business competitive and improve customer satisfaction.
How does Business Intelligence work
1. Data sources
Data can be gathered from different platforms (cloud repositories, relational and non-relational databases, external files) and can be of various types and formats, structured or unstructured: Big Data
2. ETL (Edit, Transform and Load)
ETL operations can gather data from different sources, apply the necessary transformations and load information on the chosen destination. ETL tools can be easily automated to keep the report data up to date.
3. Data Warehouse
The place to upload the transformed data. It can be a SQL Server, an Azure SQL Data Warehouse or an Azure Data Lake.
4. Data Model
To correctly respond to the business needs, a data model is created by finding and selecting the useful data, creating relations and structures to train the model itself.
5. Data Analytics & Reporting
The model is used to create reports and analyses based on the shared data.
Benefits
According to IDC, Data Analytics are a priority for the investments in all industries, since they are important tools to monitor corporate processes, human capital performance, demand dynamics and risk factors.
Goals
By using Analytics, corporations aim to boost Digital Transformation processes, more in particular the ones that can improve the offer of digital and customer-centric services.
How you can get the real, hidden value of corporate databases
Our team of Data Scientists decided, amongst all data analysis tools that can create, view and share reports, to focus on Power BI by Microsoft, in order to analyze and transform a wide quantity of structured and unstructured data in strategic information for businesses. Our real aim is to provide reports, stats, indicators and charts that can help decision makers take the best choices to improve the business and make it more competitive.
Case studies
Fashion
Visualizzazione (suddivisa per fascia d’età, genere, fasce di orario, giorno, settimana, mese) dei seguenti Analytics:
- Number of entries
- Best sellers (divided in categories and subcategories)
- Time spent in the store
- Customer flow through the store
Logistics
Reports for suppliers performance in a warehouse:
- Number of items delivered by supplier
- Drill down of item categories
- Average suppliers’ rating
Education
Reports about Bachelor Degree’s applications for a specific academic institution.
- Application analysis (divided by course and gender)
- Change in applications, compared with previous years
- Saturation rate of a specific academic year
- Change in applications, compared with the university estimates
