You might be thinking, reading a piece on how to select the right data management tool from a consulting site that happens to specialize in one particular tool could be biased. But, bear with us. We've played around with many of these tools and we've got insights to share. Our goal is not to steer you to choose Redpoint. There are plenty of fish in the data management tool sea. In this article, we'll lay out key points to consider before investing in a modern data management tool.
Tech and Sports: More Alike Than You Think
You've likely heard this analogy before, but it's worth repeating. Decathletes perform well in multiple events, but often can't beat athletes specialized in a single event. This is true in tech, too. Startups increasingly focus on delivering hyper-targeted solutions for specific business challenges while ensuring their products integrate smoothly with the rest of the tech stack.
The magic word here is flexibility. Be nimble. Or as we prefer, be agnostic.
Investing in an enterprise-class data management tool is not a decision for the next couple of years. It's a long-term commitment. So, make sure you choose a tool that performs well and can run in any environment, be it OS (Windows, Linux), cloud, co-location, or on-prem.
Identifying the Right Tool and Finding Reliable Information
Vendors often get creative with their product names. Alteryx, for example, calls their enterprise data management tool "Alteryx Analytics Cloud Platform". Then there's Hitachi Vantara's "Pentaho DataOps Platform Software" and Talend's "Talend Data Fabric". It might sound confusing, but fundamentally, these tools serve the same purpose. If you're unfamiliar with the data management domain, they might seem as different as accounting software and a CRM system.
Commonly, these tools are categorized as ETL (extract, transform, load) tools. However, this is a somewhat outdated term. A more modern alternative is Data Management Tool, and the key features to look for include data integration, cleaning, and organizing capabilities, which all the aforementioned vendors offer.
Cloud Vendor Tools? Not So Fast.
"Wait, aren't we all migrating to the cloud?" you might ask. The short answer is yes and no. Think of it as diversifying your investments. Don't put all your eggs in one cloud-shaped basket. Particularly not for this kind of tool, which is likely your stack's MVP.
"Why not choose a cloud vendor's data management tool?", you might wonder.
Cloud: Not Always Silver Linings
Although cloud vendors boast worldwide, heavily fortified data centers offering near infinite storage and processing scalability, customers are increasingly realizing the steep price of this convenience. As a result, businesses are rethinking their data storage strategies, some already opting for the cheaper route of buying their own servers for co-location. It might sound like a hefty initial cost, but hardware providers like Dell even offer in-house financing and affordable payment plans.
Without concrete numbers, "expensive" remains vague. However, we know companies that have migrated from cloud to co-location, reducing their monthly processing costs by 85% over a five-year hardware cost distribution period.
This isn't to say all cloud services cost 6.6X more than alternatives. But it should make you think twice. Conversely, if a service seems too cheap, remember the old adage "you get what you pay for".
Cloud Tool Compatibility: Not as Universal as You'd Think
Even though AWS Glue and Azure Data Factory both utilize Spark and Python, their GUIs are different and optimized for integration with their own respective services. The more you invest in one vendor's services, the deeper you get into their toolbox, making it harder to switch.
Ease of Use
The no-code trend is on the rise, and many leading tools offer easy-to-use graphical user interfaces (GUIs) for non-coders. Don't mistake no-code for simplicity or a lack of features. The most powerful tools often come with a user-friendly GUI, and we strongly recommend opting for a tool that not only has an intuitive interface but can also accommodate special python scripts if needed.
Reusability
Reusability is often overlooked in the data sphere, perhaps because many data engineers don't have a background in software programming. However, some tools offer the ability to create reusable data processing objects, which will save your team a significant amount of time in the long run.
Scalability
Choosing a data management tool that can scale with your future growth is critical. Consider the tool's ability to handle increasing amounts of data, manage complexity, and maintain high performance over time. Think about its potential to manage data efficiently as your datasets grow, its capacity to integrate new data sources, and its adaptability to add new features or modules in line with evolving needs. Redpoint Data Management excels in both reusability and scalability.
Price
Assessing the cost-effectiveness of a data management tool before investing is crucial. While an attractive initial price might catch your eye, don't forget to factor in the total cost of ownership, which includes licensing, implementation, training, maintenance, and upgrade costs. Avoid being swayed by low-cost solutions that might lack essential features or scalability options. Instead, find a balance between price and functionality, keeping in mind that a quality data management tool can provide substantial ROI over time.
Comparing Tools
For comparisons and evaluations of data management tools and other software solutions, sites like Gartner, G2, and Capterra are often utilized.
Advisors
Finally, when companies lack in-house expertise on a topic, they often turn to the consulting world for help in choosing and implementing a solution. However, it's important to be cautious about the type of consulting firm you're dealing with. Are they closely affiliated with specific vendors, or can they offer a neutral viewpoint. Many consulting websites flaunt badges like "Vendor Certified Gold Partner" and similar accolades. Although this is often intended to demonstrate their expertise with the Vendor stack, it could also suggest a potential bias in their recommendations. Maybe their suggested path is the right one for you, but it's probably not the only choice, especially on this specific topic.
So, where do we stand in this scenario? Our company name itself reflects our preferred tool. Yes, we have an obvious bias towards Redpoint, and it's primarily due to our profound admiration for this tool. Our relationship with Redpoint at RPDM Consulting is purely vendor-customer. We chose to create a consultancy focusing on a tool we genuinely believe many organizations will find valuable and seek expert advice on how to maximize its benefits. We’re not a distributor.
Summary
Choosing the right data management tool requires careful consideration of numerous factors, including vendor independence, scalability, cost, ease of use, and reusability. Shifting away from cloud vendor tools can provide cost benefits and flexibility. Ensuring scalability means your choice can adapt and grow with your data needs. Always look beyond the initial cost to consider long-term value. Finally, make sure your chosen tool offers a user-friendly interface, supports reusability, and aligns with your specific business needs. Comparison sites like Gartner, G2, and Capterra can provide valuable insights in your decision-making process.
