Data integration and data analytics – essential for better business decisions
We are convinced that the future belongs to people who recognize the potential of data. Who understand it, and who draw the correct conclusions. Companies with successful business models know how to use data for better, more targeted and more profitable solutions – from services through to products.
Two factors are significant here: firstly, access to data, and secondly the understanding and the technologies to be able to draw findings from it. Ubilabs offers support in the form of an optimized data strategy, powerful platforms and smart tools for insights that show the way forward. So that decision-making processes progress faster and more efficiently towards innovations. The future is not waiting for us; it began long ago.
And: as the first Google Cloud partner in the German-speaking world, Ubilabs has been given the distinction of ‘Specialist for Data Analytics’.
Step 1: Data strategy: digital schedule made to measure
Data is the fuel of innovation. It is considered one of the most precious resources we have for very good reasons. Data helps us to understand customers better and to offer services that they want and need. Whether it is a matter of capturing new business segments or optimizing existing processes, the task begins in each case with a smart data strategy, a clear objective and the correct choice of technology. On this basis we determine the largest possible intersection of need, potential data sources and methods of analysis – for companies in all industries.
Developing the master plan together
A data strategy is effective when it is coupled with a corporate objective and is thus oriented towards the correct priorities from the outset. For this reason, our first step is to carry out a detailed analysis of the status quo (use case) and to closely examine the existing data stock and the company’s data management:
- Data exploration: which questions need to be answered?
What data is present and in what form?
- Architectural diagram: is there a data warehouse? How is it structured? Or does it first need to be built?
On the basis of this information we work with our customers to develop an individual data strategy – supported by our team of data experts and flanked by intensive training events and workshops.
Step 2: Data platform: the bridge from the source to the user
Once the strategy is in place, data platforms come into the picture. These enable consistent management of all data workloads – from data warehouse and data lakes through data engineering and analytics to application development. On top of this, data can be read, processed and evaluated from anywhere in the company. In combination with smart business intelligence (BI), data platforms facilitate decision-making processes. New potentials are indicated and reports can be prepared faster and more accurately thanks to automated workflows.
Speeding up reporting and analyses – with Looker
We use the BI and analysis tool Looker. Our team of certified Looker developers, data scientists and data engineers supports businesses throughout their entire data journey. With company-wide data governance and access management, Looker allows data, diagrams and dashboards to be shared throughout the company. Authorized users meanwhile work entirely with original data: a ‘single source of truth’ that allows all users to draw on figures that are constantly updated and from the same data pool.
Step 3: Data insights: big data brings big findings
Static data, dynamic data, historic data, future data – we know which are relevant for our clients and what they reveal. And so, following the strategy and platform development steps, we apply an innovative analysis software suite that draws valuable insights from the data.
Individual solutions for smart data analysis
The Google Cloud Platform (GCP), with its wide offering of big data technologies, makes even large data volumes from various sources straightforward to work with. Regardless of how high the workload, GCP offers a secure, scalable and reliable infrastructure for company-related data analyses. As true GCP nerds, we additionally support businesses with the following Google Cloud services:
- BigQuery for large data volumes
- BigQuery GIS for geographic data
- Cloud DataFlow for data preparation and merging
- Firestore, the real-time database for dynamic assets
- BigQuery ML for machine learning-based forecasting
- Looker for business intelligence and analyses
Individual dashboards: all data in view at all times
Dashboards are to data analysis what the cockpit is to an aircraft. They make important information intuitively accessible. What is happening where – and where is there a need to take action? Answers arise through visualization of relevant indicators on an individual dashboard. This lowers costs and brings entirely new insights. An enormous growth in knowledge that makes effective decisions to be made early on – thanks to the automation and transparency of data. Parking management, for example, benefits from the use of dashboards by making parking data and needs for action visible - as in our project with Telekom.
How we build a data control center
There are three different approaches to creating dashboards: we use existing BI tools, we create a data analysis platform such as Looker, or we develop missing individual components ourselves.
Whether it's new mobility concepts or smart city approaches: Because every company has different requirements, our dashboards are customized to each specific use case. Geographic or dynamic data, real-time analyses and particularly large data volumes with many attributes: the more complex the data, the more important is efficient individualization. We proceed as follows:
- With real-time maps, to follow the positions of assets (e.g. cars or goods)
- With data aggregations (heat maps) to display the distribution of events on a map
- With historical data, to understand developments over time