What Is Data Management and Why Is It Important? We live in a world where data is everywhere.
Unbundling Data Pipelines: How plug-and-play will disrupt the ETL data transformation landscape in 2023
The world of transportation has been going through a smart mobility revolution. Nowadays, many people are rethinking the necessity of private cars to get “from point A to point B” due to alternatives offering lower costs, more flexibility, and less air pollution.
Why pay in excess for a car, service, insurance, and parking when the alternatives in today’s transportation landscape will still get you where you are going?
The data market is not much different. Companies today are interested in bringing their data “from point A to point B” in a fast, simple way, offered at a reasonable cost and adapted to their business needs. If so, why do we still invest in infrastructures with high costs and large commitments that are unable to cope with the frequent changes in the world of data?
Need to Commit? It’s Time to Quit.
These large commitments were once a requirement but as we move forward, they will merely be a suggestion. The majority of data players demand monthly fees, credits, and complicated billing structures to utilize their services. These crazy billing terms and resulting invoices are susceptible to spikes. When one test is performed or one safeguard fails, bandwidth amounts can skyrocket leaving employees on the edge of their seats worried about the next data bill.
Testing without needing to fear bandwidth charges is one future change we are all looking forward to seeing. As more players enter the market, fixed price solutions that charge based on variables other than bandwidth will become the norm. The monopoly style, large commitments with crazy pricing models, that we have somehow gotten used to – should die down and hopefully, stay there.
Agile is the New Reliable
Older solutions are all-encompassing and once you begin your operations with one, utilizing third-party software, and platforms, or attempting to change providers is seemingly impossible. The future of data pipelines shows us more agile and customizable solutions that can adapt and pivot to ever-changing company needs.
These smaller, easily adaptable alternatives with simple or even zero implementation requirements can scale and shrink, be moved and reconfigured easily, and be utilized by multiple team members, not just data engineers themselves. The ability to blend, enrich and manipulate data was once only possible for the code-savvy—this wasted precious engineering time on processes that could have been done by other data citizens.
Multiple players being able to take over individual processes means agility. Features such as this allow companies to derive wanted results while saving time and money. Newer alternatives mean the ability to use valuable human resources for alternative tasks that actually add business value.
No More Sacrificial Data Stacks
Forward-thinking used to mean sacrifice. It meant giving in to the rules and requirements of companies and solutions that played referee, or, finding alternative solutions – if your stack allowed for it. Data stacks are complicated, no matter if they are modern or traditional, they contain multiple individual processes working together for an architecture that rarely bends and molds easily.
In the past this meant that any changes or alterations required a sacrificial lamb of sorts, saying goodbye to older solutions that didn’t work or weren’t agile enough for changing or future business needs. Newer solutions are less pipeline reliant as they snap into existing workflows meaning that the ideology of the sacrificial lamb can stay where it should be – in ancient times.
A Dream Come True: Plug-and-Play
Today, in the world of data pipelines, there is no choice but to purchase a “car”. The associated costs of ETL products and services along with their many limitations have taken center stage. Bandwidth-based pricing models, limited integration offerings, and suitable third-party options have become the norm. With only a few big players calling the shots, complex, non-customizable, all-in-one, commitment-heavy solutions were the only options. However, now, we have a choice. Here is how plug-and-play will be disrupting data transformation for the better.
ETL data pipeline solutions that are modular, and allow for the quick easy modifications we require, with nothing else, are the epitome of unbundling data pipelines for the better. User-friendly interfaces with complete visibility, provided as a modular toolbox with no strings attached, is where the data transformation landscape is heading. Easy adoption is key and technology that can be used by every data player, frees up time for processes that matter, not just routine pipeline maintenance. Rather than committing to a costly private vehicle and committing to a long-term headache, it’s becoming commonplace to go from ‘point A to point B’ using future-forward alternatives that don’t demand a sacrifice.
Disrupting the transformation landscape is the modular building block solution that snaps into any pipeline with no commitment required.
Working with older pipeline architectures, while capturing the advanced capabilities required for today’s desired data flows is where the industry is headed. Endless customizable possibilities for any skill set wrapped up in a small easy-to-use package that is not resource-intensive or constraining for engineers and end-users alike is the disruption we’d hoped for.
Developed to help you deal with the changing needs of the data world, discover the plug-and-play solution that doesn’t require big commitments or large investments. Datorios offers the flexible, easy-to-adopt, non-committal, and affordable toolbox, that will help you solve your data problems now and as you evolve using the most advanced transformations available, without the headache.
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