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Understanding the Data Pipeline

Understanding the Data Pipeline, Data Pipeline, Data collection, Data storage, Data Analysis

“Knowledge is power.” This old adage has been given new life in the digital age, as data is now a hot commodity among many organizations. Data is powerful because it allows a business to refine their existing strategies and establish new ones with the aid of information on a number of topics. However, the processing of data is one that consists of multiple steps and requires a particular set of skills. Here are the points to remember about the collection, storage, and analysis of data.

Data Collection

Data collection is the first step of the data pipeline, and it appropriately forms the foundation of the entire process. Data is everywhere, and data collection methods are many. For instance, network protocols like Netflow monitor network traffic in order to ascertain important data points. What is NetFlow? NetFlow is a network protocol that tracks users’ IP addresses in order to assess traffic volume and patterns in order to inform network operators of various factors. For instance, a business can make use of this kind of monitoring to determine the security of their network at high volume times, as well as anticipate potential hackers by observing suspicious behavior on the part of a given user. They can use that same information to come to the conclusion that network traffic can potentially be spread out or concentrated by employing different marketing techniques. Data can also be collected and utilized automatically by an algorithm for purposes like targeted advertising, and it can also be gleaned from on-site records like those sales.

Data Storage

Data storage has long been taken care of via physical storage methods. That is to say, that printed or written documents could be sufficiently stored on site until the fairly recent data boom. Modern methods have outmoded the old techniques to such an extent that physical file storage is quickly becoming insufficient. Cloud storage provides a clear solution to this problem, however. Cloud storage is the process of storing files on remote devices in the cloud, and this provides several data storage advantages. For one thing, cloud storage can be expanded upon far more than a single on-site device and perhaps even more than your entire network, because it doesn’t depend on singular devices. The data in your cloud storage can serve as backups of what’s on your drive in case of emergencies, but it can also be the one place that most of your data is stored, depending on your needs. Cloud storage also makes the sharing of files much easier, as anyone with the proper credentials can access the files, which is much more efficient than emailing or hand-delivering pertinent documents.

Data Analysis

Data analysis is the part of the data process in which otherwise meaningless numbers are given context, at which point the meaning of said data becomes clear. In some cases, a basic understanding of numbers and math is sufficient for determining data trends, but it is generally accepted that a competent data analyst is required for the bulk of modern data interpretation. In fact, data analysts are in higher demand now than ever. Data analysis is also a resource-intensive process that incentivizes the use of cloud computing. Cloud computing is the process of linking multiple devices in the cloud, and this allows these devices to share computational resources in order to accomplish difficult tasks much more quickly and efficiently.

Upon successfully interpreting a data set, that information can be used to improve your business in several ways. For example, marketing strategies can be tailored to target demographics that aren’t currently interested in your brand, but knowledge of who is interested can also be utilized to refine existing products, services, and marketing campaigns. Data offers a business the proverbial “keys to the kingdom,” but only with the advantage of understanding. With these tips in mind, you can refine your data pipeline in order to garner pertinent information and develop winning business strategies.


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Four Steps to Effective Data Management

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