Development of a hybrid solution to be able to detect swimming pools in different regions
Tag: information
Big data and the traps of spurious correlations
In Spain, it is estimated that around 68% of industrial companies are considered "digital novices" or "digital followers", which indicates that they have not yet fully adopted digitalization in their businesses and need to do so to improve their competitiveness. When analyzing large data sets, we warn against finding spurious correlations, where variables may appear related without having real meaning or where a third variable could be influencing them. Therefore, it is essential to interpret the data with caution, remembering that correlation does not imply causation, and to be aware of how graphs and visualizations are constructed to avoid erroneous conclusions.
SMEs and Big Data: 4 axes to start 2023 with a solid data strategy
The majority of Spanish SMEs trust in digitalization and plan to invest in it in the next three years, however, they still need to carry out a digital transformation focused on the efficient management of large volumes of data. Using Big Data strategies can help these companies proactively address problems, generate new opportunities, improve operational efficiency, and build customer loyalty. However, SMEs face challenges such as the integration of different data sources and types, the need to process large volumes of data quickly, and the proper selection and preparation of data. To succeed in a Big Data strategy, SMEs must clearly define business problems, select and prepare the right data, store it securely, and perform extensive analysis to make data-driven decisions. The beginning of a new year is an opportune time to implement digital transformation and Big Data strategies, which requires a change in mentality and strategic focus in these companies.
Data policy: owning your information as the key to the process
Data science strategies are increasingly used by Spanish companies, with a positive impact on organizational performance and higher levels of resilience. It is essential that companies own their data and ensure its quality, and that they adopt a data-driven approach to make strategic decisions based on data analysis and interpretation. Proprietary data management provides flexibility and capacity to address present and future business needs, but requires a data governance policy and adequate attention to data integration, quality, and management.
Are there differences between a CRM and a CDP?
Both CRM and CDP technologies are valuable tools, but for different purposes. While CRMs focus on managing customer interactions, CDPs focus on collecting and understanding customer behavior data. The choice depends on the specific needs of each company and sales and service oriented roles can benefit more from a CRM, while customer management strategy oriented roles can take better advantage of a CDP. Ultimately, it's important to assess what kind of information is needed and how it will be used to make more informed business decisions and deliver personalized customer experiences.
How Big Data is driving retail transformation
The use of Big Data in retail unlocks valuable information about customers and improves decision making. It allows you to understand purchasing patterns, optimize inventory and personalize customer interactions. Additionally, data analysis helps predict trends, adapt to market changes, and improve customer satisfaction, generating revenue and competitive advantages.
Data drives the connected apparel revolution
The fashion of the future focuses on the functionality of smart clothing, which integrates electronic components and sensors into fabrics. These sensors capture data from the human body and are sent through apps on smartphones, providing information on sports and health metrics. Examples include yoga pants that improve posture, socks that improve walking and running technique, and smart socks that detect ulcers. The smart clothing market is projected to reach $5.3 billion by 2024 due to growing demand and technological advancements in data capture and monitoring.
