Data revolves around technological advances, but many companies still need to realize what this journey can provide.
With a data science-centric mindset, improving every area of the organization is possible. In this context, we will discuss the importance and how to apply the data journey in your company.
Why Is The Data Journey So Important?
Companies need to think about collecting data, how to transport, protect and store it, but also how to get it sent.
This information makes the data journey a vital step; everything must be forwarded to the correct platforms. Allowing processing and analysis capable of identifying what is valid.
We can understand the data journey as fundamental to transforming information into business intelligence. Thus, acquiring the necessary inputs for decision-making.
With an increasingly technological market, data has become fundamental for organizations, whatever their size, type or sector. They are the most significant business assets, products, and services.
Understanding The Data Journey
Known as Data-Driven Culture, it is the moment when the company incorporates data for decision-making.
This means it is based on a long journey, from understanding the business and capturing data to a complete analysis of all areas.
However, to understand this journey and make it generate good results, you need to understand your needs. And that’s the only way to set the goals that must be achieved.
Each sector must have investments so people have access to specialized training. In general, it is a process of cultural transformation and acts to convert data into relevant information to be used strategically. Thus, companies can make the best decisions.
How To Apply The Data Journey In Companies
A data culture will not form on its own. Therefore, it is essential to understand ways to help create this journey.
Next, check out five tips that will help you promote these actions in your company. Follow!
#1 Collect The Data That The Company Already Has
Every company has its data. The first step to applying the journey is to use the information your institution already has.
Collecting this data will gather information from all systems, spreadsheets, ERPs, CRM, or any other data type. The focus is on keeping inbound pipelines organized.
#2 Enrich The Data With Other Relevant Information
In addition to the company’s data, integrations with the Internet of Things, Sell-Out data and data not yet explored are used.
Other data is also relevant and can be accessed in various ways. For example, through public websites, market studies, and surveys to extract data with email marketing, social networks or public texts, videos and audio from podcasts.
This information is structured, corresponding to 80% of the company’s data; therefore, it needs structure for the next steps. Always keep them organized and in reliable hands.
#3 Centralize All Data Journey Collection
At this stage, there is the flow of reliable data, where we must assemble a structure and thus end data silos by detecting anomalies.
The process is called Data Quality and aims to ensure the data arrives correctly in the company’s strategic decisions. Always remember that your applications’ quality results from your data’s quality.
#4 Catalog The Data
It is nothing more than creating a corporate-scale secure repository of all the data the company makes available for analysis.
This gives consumers a single catalog to find, understand and gain insights from any corporate data source.
Mounted on data security platforms and with governance features, it is possible to integrate any tools that manage data efficiently;
Promoting enterprise-level scalability, reliability and performance, thus delivering exponential enterprise growth.
#5 Select The Best Data Analysis Tools
The tools are the most diverse: from a/b tests to identify the best logo to CRO resources to identify the site’s performance.
Currently, business areas have new needs. And for this reason, it is necessary to share and catalog data to have freedom in a scenario that does not stop changing.
This step is the most important, as it creates new views without relying on IT based on data and allows the company to be part of a data journey.