Turning Big Data Into Smart Data

Big data is an increasingly widespread practice in the whole world nowadays. A record amount of data is being produced every second by different devices and sensors. Gathering and analyzing this data to convert it into valuable information is giving businesses more benefits than ever.  But making sense of billions of unstructured data pieces can be difficult and consume a lot of time without the right technique, precise and correct tools.

Learn more on Service Assurance in the access network space, and how to transform it to go from simply collecting data to actionable intelligence, with our Turning Data Into Actionable Intelligence Webinar

The million-dollar question is: How do we convert big data into smart data? What parameters can be analyzed?

Artificial Intelligence makes it possible to manage the challenges of big data. By making simple data, smart, new opportunities are revealed. The added value resides in a better decision-making process, more timely actions, and customized solutions at large scales.

Five Steps to Convert Big Data Into Smart Data

Social media data is everywhere in the form of Facebook, Twitter, and Instagram posts, blogs, search engines, forums, and a wide range of other content pieces.

The first step is collecting all the data about a certain topic. By searching on a specific issue, the amount of data should be as big as the list of URLs or posts and more. Adding many different types of filters is the next step. The time frame can be the most basic filter. Information should be filtered according to each project’s needs. Other useful filters are those based on the type of media channels like Facebook, Twitter, forums, blogs, YouTube, or by the post’s language and origin.

Adding more filters can convert unstructured Big Data to manageable smart data. The filters help in getting a good idea of exactly when and where a particular topic is coming from. Yet, the most important filter is cleaning the noise and fraudulent data. At this stage, you have a good idea, but it is necessary to deepen in this ordered data to get accurate and functional data.

To ensure the right data is collected, the right skills during the analysis stage are needed. Skills relating to market research, along with exceptional analytical skills, are a requisite for data analysis. These skills help in understanding and analyzing large data sets. Some research agencies are now equipped to capture big data and add information daily.

 Combined data from different sources results in better decision making. Combining mighty data with vanguard tools provides a more accurate view of customer behavior. Analysts have the right tools to gather the correct information. Yet, they need exceptional skills for the analysis; they are now better equipped to handle large data sets. At this point, the analyst can use the AI to make the process easier and faster to convert big data to smart data. This way, information can help people and businesses to make decisions based on more relevant data. By using the right tools, skills, and AI, we can quickly analyze the filtered information to create valuable resources. Every level of filtering and analysis gives key information about social data. During this process, disordered and unstructured data gets smarter. Once data is refined to this level, it can be used in countless ways.

By using advanced analytics, the decision-makers can make the right decisions for their companies.  For example, this information is useful to measure and analyze the performance and effectiveness of the market and enhance return on investment (ROI).

The process of searching, filtering, and analyzing big data is a valuable source of information to the companies. Through these tasks, businesses can get crucial and detailed information about their customers. At this stage, data values should be involved in business strategy development to become smart finally.

At the moment, the final decision to use and incorporate this valuable and structured information into business strategy falls in people in the company with expertise in each area: “the decision-makers”.

The process to transform Big Data into Smart Data today isn’t perfect, but it improves day after day. Even so, it is an essential tool for business decision making today.

Smart data helps to build healthy relationships between the companies and their customers. The information is centralized, valuable, and context-based with respect to the customer’s thoughts and behavior. Smart data improves customer experience and helps to promote trust between the customer and the company.

Learn more on Service Assurance in the access network space, and how to transform it to go from simply collecting data to actionable intelligence, with our Turning Data Into Actionable Intelligence Webinar


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