Why Charter Networks Are Investing Heavily in Big Data
What are Charter Networks
Charter Networks are simple networks designated for management of schools / colleges to boost academic performance. This is something which is meant for everyone related to schools and colleges. It affects not only students, but also teachers and staff meant for administration.
These networks are responsible for making processes at schools and colleges smooth so that students can directly benefit from it. One of the major grey areas figured out at management of any school or college is the management and a performance check for students. Earlier, hiring different counselors was a major step to tackle this situation. But later it was realized that a machine with fixed set of parameters can propose better solutions because it will be free of any biases and can depict actual data in a much readable format on which further actions can be taken by teachers or staff of such organizations. This seems to be more efficient than any other alternative because of assessment of performance on a standard set of rules.
What is Big Data
As the name suggests big data can be simply defined as extremely large data sets that can be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. This is especially significant when volume of data is huge and needs to be managed in a better way. Traditional, approached to handle such huge amount of data delivers a poor performance which led to invention of more scientific ways to handle such data. Nowadays, big data is part of our daily life. Any sponsored ad that you see on Facebook or any other app is nothing but a result of analytics on some big data stored at one place or at different places. Big data has opened a new world of opportunities to define patterns in data and get optimal solution from it.
Advantages of Big data
- Volume: The biggest advantage of big data is to cater huge volume of data. This is a very common case when sources of data include a lot of variety. With big data, scopes have only widened for analysis of such huge chunk of data.
- Velocity: A challenge that comes along with huge chunk of data is the speed with which data needs to be processed. With big data, the performance has increased to a much better result set.
- Variety: Usually data comes from different sources and each source delivers data in specific format that need not be like other sources in most of the cases usually seen. The challenge becomes complex when this raw data comes in an unstructured way like that of an audio file or a video file or a word file. Along with big data, the standardization is now possible with better results for end users of any organization.
Need of Big Data in Charter Networks
Let us try to understand the relationship between Charter networks and Big data. Now we know that charter networks work on data related to students and teachers. This data is not as simple as it may seem at first glance. The result delivered by any charter network is something related to a pattern, trend or statistic. But this result comes after a lot of analytics on data from different sources. Some of the sources include students monthly / quarterly assessments, students’ feedback, teachers’ feedback, overall curriculum, curriculum progress status, students’ non-academic interests, students’ performance in non-academic activities, students’ performance history in previous semesters, etc. As you can imagine how complexity increases when someone tries to merge this data into one unit to give a definite result. Also, when number of students increase then the quantity of this data increases manifolds. Also, it is worth mentioning that previous data of any student needs to be stored to determine the future trends hence this data will gradually only increase with each passing semester. Even after a student has passed the school, some of this data needs to be retained to track performance of teachers for future analysis.
Charter Networks and Big data relationship:
Now, we can easily understand the need of Big data in Charter Networks. Going by the obvious market rule of demand and supply, the scope has even got deep rooted. With technological advancements and enhanced security in Big data, investment on getting a big data software solution model is very common in charter networks. What started as a small industry has seen a new range of possibilities because of integration of big data technologies. The solutions now are not only faster, but provide a lot of deep insights which were earlier not possible. The performance has increased to a large extent and with increasing performance the deliverables have also increased in shorter span of time. When charter networks were introduced, a lot of criticism came along with it. Many think tanks thought that it was just a way to earn money by showing a very usual monitoring of data. A lot of people even had a perception that school and colleges are better not administered by machines. It took a lot of years of patience and continuous commitments to change this perception. When these networks started delivering the results, then only people realized that performance monitoring has helped students and teachers a lot. It has acted as a tool to measure a lot of parameters in which a student, teacher or even an entire school / college can be judged. Now that acceptance has come in society for the same, charter networks must move ahead the road to sharpen the results. This is where big data came into picture. And now it seems like it has taken over the screen as a major player to rely upon.
Any technological solution that caters to any organization needs to advance gradually with the market. If charter networks won’t invest in big data then the negative impact can take down this whole industry by a blow. Because in the end the survival of fittest is the only possibility. Data will never be static and so should not be the technologies which are doing analysis on this data. Investment by Charter Networks in Big data is a welcome step for everyone.