3 min read
Scroll to the bottom for a summary.
Ask any data engineer, scientist, or analyst, and they’ll tell you how essential it is to have agility in your modern data architecture. Changes are happening fast, and business teams are demanding more data by the minute. An agile data architecture is the number-one tool you need to become the hero of your business – not to mention, with the right tools you don’t need a large data team to make a gigantic difference.
Agility in data architecture starts with understanding the data itself. It's important to know what data is being collected, where it's coming from, and how it will be used. This information can be used to design a data architecture that is flexible enough to accommodate changing data requirements. If you don’t know where your data is coming from or what you need it for, there’s really no point in having it at all – you may as well hang up the keyboard and mouse and start a chicken farm (nothing against chicken farms – they too require data).
add new data sources
Throw your feet up onto your desk for a moment and imagine this – you have just finished manually coding the perfect pipeline to connect all the software your company uses into an organized data warehouse that flows straight through to visualization. The connections are working great, the data is flowing perfectly, and reports are generating like magic. Nice work, my friend!
Out of nowhere, a dark figure appears in your doorway. It’s Carl from Sales. He is here to tell you that the decision has been made to implement a brand-new CRM and he wants to know how quickly you can update those fancy reports he likes so much. Goodbye complete pipeline, it’s back to building for you.
What if changing or adding data sources was the click of a button instead of months of work? One of the key aspects of an agile data architecture is the ability to add new data sources with super-human speed. With the ever-increasing volume and variety of data being generated, businesses are adding new software and technologies fast. This requires a data architecture that is flexible and scalable, so Carl can change his mind as much as he wants, and it won’t cause you to imagine his slow demise in your head as he speaks.
TimeXtender allows for multiple data sources to link in one instance or at various instances, eliminating the tedious wait time for sources to connect to your data lake. And with more than 250 compatible data sources, you can now focus your time on innovating instead of implementing.
analyze this
We don’t know about you, but we’ve heard the words “data-driven decisions” about a thousand times too many. We’re not saying data isn’t important for making decisions, but what we are saying is that decisions still need people to make them (and we also hate overused buzzwords).
"You...you. You've got a gift, my friend."
As a data professional, it is your job to give those people the best data possible to help them make educated decisions to grow the business. And since those people are humans, that means they change their minds… a lot. An agile data architecture such as TimeXtender can provide the necessary framework to handle large amounts of data and the necessary tools to prepare and transform the data in minutes.
No more waiting around for execution to finish or tables to generate – TimeXtender will have your data ready to analyze before your Cup O’ Noodles is hot.
secure your data
In September 2022, a telecommunications company in Australia called Optus was the victim of a cyberattack that leaked the personal data of 9.8 million customers. 2.1 million of those customers had important personal identification information stolen. The attackers then tried to extort the company for a $1 million ransom. Yikes!
Optus is far from alone! Breaches like this are happing every day, and although not all businesses store this level of personal information, all businesses still need to be very aware of the security of any data they maintain. This requires a data architecture that has robust security controls in place and can quickly respond to changing security requirements.
It is also important to mention the advantage of employing a holistic solution for your data pipeline. Instead of stacking a bunch of vulnerable software together, each managing a small part of your data pipeline, why not choose a tool that does all of it? Ingest, transform, prepare, deliver, and protect your data with one tool.
The importance of agility in modern data architecture cannot be overstated (but we may still try). An agile data architecture that is flexible, scalable, secure, and able to incorporate new data sources quickly can provide organizations with a significant edge and allow them to make the most of their data assets. Whether you’re a data engineer, scientist, or analyst, agility should be a key consideration in the design and development of all your data architectures.
Summary
Agility is key in modern data architecture. This post looked at three important factors to consider when building and designing a data architecture that's flexible and agile.
1. New Data Sources - It's essential to be able to add new data sources with the click of a button, instead of spending hours or days building new pipelines.
2. Analyze This - People are still needed to analyze data and make decisions based on that data, which means you need to be able to prepare and transform the data in minutes, not days.
3. Data Security - Breaches happen all the time, which is why it's important to have a secure data architecture that can't be compromised by cyberattacks, faulty software, or distracted employees who leave their password on their desk.
