Post by account_disabled on Feb 20, 2024 1:24:16 GMT -5
We have seen on previous occasions how, to what extent and why data quality plays an increasingly central role in the consideration of the data that an organization has. Let us not forget that data, especially in Business Intelligence and advanced analytics contexts, becomes one of the corporate assets that can offer the greatest opportunities for growth and expansion, support for decision making and competitive advantage, and that paying attention to the quality of the same, especially those coming from sources such as social networks (sources that provide great variety and volume of data, at high speed, but often with reduced or compromised quality in some way) it becomes a critical issue to get the most out of them.
Data quality: the importance of quality in data from social networks It is estimated that more than 90% of companies consider data fundamental to developing their business model, minimizing risks and maximizing the use of opportunities, but that practically 70% of them lack the necessary instruments to do so. That is, only 30% of business organizations would have the necessary tools to get the most out of their data , a problem that increases as the volume and variety of data hosted in corporate databases increases. The concept of data USA Student Phone Number List quality comes powerfully into play in this consideration which, as we have reviewed in other moments, has a double facet . On the one hand, there is what we mentioned a moment ago, and the consequent need for the data housed in corporate data warehouses and the tools to structure, analyze and transform them into sensitive information for the organization respond to an adequate and coherent approach, to a corporate data management strategy that allows you to get the most out of them. In this sense, we recommend the guide 10 keys to defining your corporate data management strategy , available completely free in the ebooks section of this same portal.
On the other hand, of course (and what we are interested in discussing today), is the quality of the data itself, that is, that it is complete, its duplication is avoided, and the necessary tools are available to ensure the highest degree of veracity possible. .. and, of course, take effective measures to clean data that may cause conflict when undergoing analysis. Among the main reasons that can compromise the quality of data from social networks, and that must be considered in different ways when configuring the relevant filters (one of the most effective ways to carry out adequate data cleaning ), are: Consistency : data that comes from social media sources usually present little integrity and a fairly high level of contradiction, the result of the very dynamism with which social networks operate (and, consequently, with which they provide new data). Integrity : the anomalies of data obtained through social media channels are usually quite high. Uniqueness : a key issue, since it refers in the first instance to the non-duplication of the data (something that occurs frequently, sometimes seriously compromising the data quality and, with it, the metrics obtained with the social media data.