Data First has been defined as an approach that ensures the highest reach of value through the shortest and most convenient delivery time.
Maximizing the use of data is something every organization aims to achieve, more so now that the amount of data continues to grow larger on a daily basis. It has been expected that by 2025, the amount of data generated worldwide will reach over 400 exabytes. It goes without saying that this would pose a challenge for enterprises. Making the most out of data garners success for organizations since the insights data generates have proven to be beneficial to enterprises.
Data First has been defined as an approach that ensures the highest reach of value through the shortest and most convenient delivery time by targeting data content. It involves protecting and regulating data, appraising the cost efficiency on the use of big data technologies, and enabling the strategic and controlled sharing of data with necessary third parties.
The main asset in the Data First approach is data. Its process revolves around understanding the extracted signals from data and making use of them. The captured data will then be inserted as a signal for algorithms and used to fuel the application. When more data is created, new signals and new forms of data emerge.
It should be noted that data should be viewed as a driver of innovative thinking that leads enterprises to advance in markets centered on data and that it should be used as a means to guide employees’ decision-making process, guiding and empowering them to make strategic choices.
The Data First applications, which embed Artificial Intelligence (AI) and Machine Learning (ML), essentially produce actionable insights for organizations by processing new data. They are built with open source processing frameworks and data warehouses for large datasets. Data First is used in different industries and operations such as Sales, Marketing, E-commerce, Human Resources, Manufacturing and Supply chains, Legal, IT Security, and IT Operations, among others.
The insights generated from the dataset are not merely derived from reports but also through the analysis made by AI and ML. As mentioned earlier, Data First application embeds AI and ML, hence, these two are significant in marking out data and creating actionable insights.
Usage differs per industry – A marketing company can use Data First in order to monitor its users on a platform, meanwhile, a supply chain company may use it to identify the weather patterns and monitor port activity. Both examples result in creating insights through the use of Data First that will help the company to make better-informed decisions that can be shared across many different users.
Data First goes beyond the scope of just tracking data since it also creates insights from it. These insights can thereafter be added to existing models or be used to form new ones which would then flow through a course that gives them meaning, context, and suggested actions to be taken. By understanding how this process works, the results would not only lead to a faster pace of delivering benefits to users but also empower enterprises' decision-making through Data First applications.
Challenges with data management, deriving valuable insights from datasets, and the security of data are among the many concerns that enterprises face with organizing and managing data. Applying and integrating a Data First approach culture can help address these problems within your enterprise. And to reiterate, this approach within your organization provides the benefits of giving meaning to your data, creating actionable insights, fast and convenient delivery of insights to users, and empowering the organization to make strategic decisions.
To know more about how you can apply Data First applications within your enterprise, feel free to reach out to One Connect Solutions.