The Evolution of Data Management over the Years
Everything seems to be moving so quickly online nowadays. This is the wild, wild west of the digital age, and data management has come a long way. With innovations in databases and solutions, there have been a lot of new features and performance upgrades. Data management today is more complex than ever before. One of the biggest challenges is managing security concerns. Preventing problems, managing security, and more are all developmental advancements that improved over the years. Let’s dive deep into the evolution of data management over the years so we can learn how data management is used today and how it will be used tomorrow.
The History of Data Management
The first mechanical advancement in data management can be traced back as far as the 180s with the mechanical punch card. Created by the company that would eventually form IBM, these punch cards were a big deal for data management. Instead of doing computing by hand, punch cards were able to record computations on a thick card.
IBM later introduced the first disk file in the 1950s. Known as the IBM 350 Disk File, this disk file worked with a mainframe computer and is the first hard drive. Though it weighed almost 1 ton and was taller than a human, it was a big stride for the recording and maintaining of data for businesses. They could record information or produce output on punch cards or print. This was a big step for technology that wasn’t matched until the 1970s.
The first data management systems as we know them today were seen in the 1970s. These was mainly just operational. They didn’t have many of the complex features we’ve come to know today. They existed mainly to provide a record for the operational state of the business. This was for analytical reasons but also for compliance reasons. Today, we still rely on data management to provide records about operational states.
These early databases were measured only in megabytes which is something that would be laughable today! Today, we use terabytes to measure the volume of our databases, but in the 1970s these databases provided mostly monthly reports. They were unable to perform complex, real-time analytics. These performance analytics were created by humans, whereas they are now mostly automated with self-service operations.
Evolution continued into storage that resembles what we know today. Software Defined Storage appeared in the 1990s to work with virtualization to manage hardware requirements and help with workload. This is the start of automated management systems and virtualized data.
Today, the most common and well-known type of data management system is cloud storage. You might be surprised to learn that cloud storage isn’t a new concept. Though it wasn’t introduced as commonplace until recently, it was actually created somewhere in the 1960s. It became mainstream at the end of the 20th century in 1999 with Salesforce.com. Salesforce introduced an enterprise application via a website, the first of its kind. This brought big leaders like Amazon in 2002 and other interested-based services later on. Today, cloud storage is the name of the game, and it’s clearly here to stay!
As you can see, data management has evolved a long way since the days of paper punch cards and heavy hard drives! Today, businesses are able to manage data virtually through the cloud, and this has helped combat a lot of the problems of the past.
Challenges of Data Management
This evolution of data management didn’t come about without its share of challenges! Even today businesses face problems with data management that future advancements will need to solve. Some of the problems of data management in the past included human involvement, size, and space.
First, most of the data management solutions of the past relied on human input and human requests. This left a lot of room for errors, not to mention it was time consumer for businesses. Another difficulty was the physical size. Things like the first hard drives were massive in size, and they came with a number of limitations. Hard drives did not become more manageable in size until the 90s. Finally, the early data management systems did not have much space compared to what we know and use today!
Just because we’ve made advancements and huge strides doesn’t mean we don’t still face problems in our own data management systems. One of the biggest problems is frequently seen by the general public on the news and has led to outcry around the world. Security concerns are becoming more pressing as breaches in data are becoming a regular occurance. It is up to businesses to find new ways to protect their customer data.
Another challenge of today is the sheer volume of data. Unlike systems of the past which only handled a small volume of data, todays’ system manage large quantities of data on a daily basis. Data is created on a number of different channels depending on the size of a business, so new technology needs to meet this need for more data storage.
Finally, one of the biggest problems of today’s data management is failing to prevent problems. Businesses and tech companies need to be proactive about solving problems before they begin, but that involves a lot of ongoing monitoring and performance. Things like java performance & monitoring tools | AppOptics and in-depth analytics go a long way to preventing problems in data management.
The Future of Data Management
As the sheer size of data continues to grow in the digital age, the future of data management looks for new solutions. These solutions will likely develop in the form of algorithms and artificial intelligence. You can see these new solutions taking form today in everything from machine logs to social media. In addition, the need for greater speed and accuracy in data management continues to grow. This will require stronger architectural systems and sizing solutions for data management.
The evolution of data management has been a long journey, but one that has introduced new levels of technology! As data management needs continue to develop, more advancements will rise to meet these changes. Data management is something that affects both consumers and businesses as we head into the future.