April 21, 2022 · 4 min read
There is a huge ocean of data out there. The sources of information are diverse, in addition to being presented in many formats; so in the digital world, the flow of data is abundant and diverse. What do we do with them? It is not enough to obtain the information, but you have to know how to process, select, transform and interpret it; extracting what the data really means, and in particular, in business, it is extremely important to interpret it properly, to guide the efforts to be directed, according to the objectives that have been defined, redesign them or even suggest new options.
In this installment, we will comment very briefly on 'data as a service' and ‘data as a product’ and our role in APSL, in this context.
Data as a service (in English it is known as Data as a Service -DaaS-) is a model for supplying and distributing information. Its heart is data management, the cloud, through software tools from where a multitude of services related to data emerge, in very general terms they are: storage, processing and analysis, for distribution in text, images, videos and sounds.
Among some examples of DaaS we can mention: the management of the data warehouse (data warehouse), the use of geographic data; financial data or business data of organizations.
DaaS provides benefits, among which the quality of the data stands out; the agility to go to the required data in a manageable and user-friendly way; In addition, the financial adaptability offered by various DaaS provider companies allows savings in operating and maintenance resources; and finally increase the workflow. In other words, it is provided upon request by companies with valuable and very specific data, integrated into their business applications.
In a very brief way, we can cite the following advantages of DaaS for companies: Low cost of equipment, reduction of costs with capital goods, free of maintenance and updates, flexible customization and information security.
We found that DaaS is linked to storage as a service (Storage as a Service -Saas-) and software as a service (Software as a Service -SaaS-).
In the context of data as a product (being its acronym in English: DaaP), the reports are the most common example, offering a display of data, usually in the form of graphs and/or descriptively. However, when various advanced analytics are incorporated, such as predictions, projections and/or recommendations, a higher level is reached, thus allowing to deliver exactly what is required by the company to facilitate good decision-making.
Other examples of data as a product are search engines; cybersecurity through threat detection; the product suggestions that are offered when we enter a commercial website; granularity (level of detail) in credit card purchase data, as well as fraud detection and customer classification; identification of diseases through image analysis and suggestions in their treatments; predictive maintenance of machines in industry; image classification; process automation; consumption forecast for the energy sector, among others.
In summary, they are applied to data projects, key principles of product development, where unmet needs are identified and addressed, agility, iterability and above all in the reuse of point solutions to solve a variety of business problems.
At APSL's Data Science Department, we employ Big Data and Artificial Intelligence and work together as a team with diversity of clients, where our valuable human capital resource has allowed us to add value, either through data management, its integration, and guaranteeing its quality during its transformation processes. and analysis through the flow of data (for example, using the framework Kedro), in order to offer and guarantee high-level consulting and administration services for Business; as well as through the management of mathematical models and intelligent algorithms, we have carried out predictive analysis, and consequently have added value to our clients, for their business strategies.
Additionally, we invite you to get to know and interact in the Spanish, English and Catalan languages, with our virtual assistant for remote teams, YedAI, which you will find in the lower right corner of this page, which is a chatbot tool based on artificial intelligence, part of APSL's investment in I+D+i focused on providing service to teleworkers of any organization. The bot has learned to manage issues such as: “Job offers”; "Organization chart"; "Contact"; "Who sends me a new computer?" “How do I request vacations?” “How can I negotiate a salary increase?”… and our Content team can easily edit the answers if necessary in the knowledge management platform.
It is important to point out that just like life itself and any learning process, it will not always be possible to obtain an answer that satisfies you, and you will have the option of giving feedback or contacting a human directly.
In a previous entry of this blog, we talked about how to pass from raw data to data with value. Now through various procedures that involve selection criteria, processing of mathematical and statistical models, together with business logic and business objectives, the data can be transformed and offered as valuable services or as interesting products that facilitate our journey in the digital world.
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