Find out how to stay on the cutting edge of Data and AI by reading the latest tips from Jim Burnham, lead trainer on Revolent’s Data Engineer course.
We all know by now how valuable data is to any business. The challenge is extracting meaningful insights from the mammoth amounts of data we generate and handle every day. The exponential growth of data generation, and the rising need for organizations to have more control over their data, have triggered a surge in the popularity of data management and intelligence platforms.
With many businesses drowning in a sea of information and struggling to extract actionable insights from the data they collect, these platforms offer a comprehensive solution that helps companies collect, store, process, and analyze data more efficiently.
In today’s data-driven world, implementing a smart data management platform is no longer a luxury reserved for the largest and most tech-savvy of businesses, but a necessity. By using these solutions to take control of their information, businesses can unlock the real power of their databases, tap into new opportunities, improve performance, and outmanoeuvre the competition.
So, in the fast-evolving landscape of data and AI, where do you start? We caught up with Jim Burnham, lead trainer on Revolent’s Data Engineer course and all-round data wizard, to get his tips on staying ahead of the curve.
Meet Jim Burnham
Firstly, let’s get to know a bit more about Jim—and what makes his insights into the world of data engineering so valuable.
“I’ve been involved in data engineering throughout my entire career,” says Jim. “I started by creating a programming language designed for loading data into databases, and since then, I’ve developed and designed data flows for over 20 companies across ten industries.”
His extensive experience in designing and developing data solutions has brought him into contact with almost every data technology under the sun, from Teradata and SQL to Redshift, Postgres, Exadata, and DynamoDB. Throughout his data engineering career, Jim developed a passion for creating innovative data solutions.
“For a long time, my favorite part of the job was coming up with data solutions,” he recalls. “A good data solution requires an understanding of the business, its project goals, and the timeline. With a good business understanding, you can design a data solution that will fit the bill using your available tools, people, and standards.”
Jim’s talent for coming up with solutions to data-related problems is underpinned by years of know-how and practical experience with data technologies. But he also understands the importance of soft skills, especially when working with multiple stakeholders.
“Implementation is a process of getting everyone on the same page,” he says, “which requires communication, teaching, building consensus, planning, and resolving issues that can prevent success.”
This knack for communicating how things work and helping others get to grips with data engineering projects sparked a new interest for Jim: teaching. “Over time, the best and most rewarding part of working on any data solution project became educating, and enabling a team to complete a project by learning new skills,” he adds.
Luckily for Jim, his dream job was on the horizon, and in 2023, he developed and delivered Revolent’s first-ever course for Data Engineers.
Where is data and AI technology headed?
We asked Jim what kind of trends, market developments, and emerging technologies he expects to see in the data and AI spaces in the near future. “Generative AI is the newest tool in the data engineering toolbox,” he says. “The ability to extract data from unstructured texts like contracts is incredibly valuable. Translation of languages is now easy; even the translation from English to code or SQL can be done instantly.”
But getting access to the benefits that GenAI can bring to a data engineering team takes some investment, especially if your business is still lagging behind on the cloud technology front. “To use it in a production setting, you need a GenAI-enabled data platform,” Jim explains.
With the adoption of data platforms within corporate IT departments still ongoing, Jim suggests businesses that want to harness GenAI in their data engineering strategies should ask themselves a few key questions before investing in data solutions:
- Will your data be stored in a solution that has built-in GenAI, Machine Learning, application, and visualization functionality?
- Will you be able to share data with your customers and vendors, and vice versa, to increase your ability to mine value from data?
- Will you be able to extract insights from unstructured data?
“Innovators, early adopters, and some of the early majority already have their data in a unified data platform,” says Jim. “It’s time for the rest to catch up. If you don’t have a cloud-based data platform already, you need to be exploring what it takes to adopt it.”
How can companies use data management solutions to maintain a competitive edge?
Adopting a data management or data intelligence platform is a big investment, but one that can pay dividends if utilized to its fullest potential. Simply implementing a data management platform is not enough; to get maximum ROI from these potentially transformative tools, you must be prepared to constantly monitor, tweak, and optimize them if you want to uncover hidden trends, identify new opportunities, and gain a competitive edge.
One of the most impactful ways you can make sure you’re squeezing the most value from your data management platform is to hire a data professional. While these platforms are packed with powerful capabilities, most need specialized knowledge and an experienced hand to be used effectively.
Hiring professionals with expertise in data management and analytics can help your organization optimize the platform, making sure it’s configured correctly and is properly integrated with existing systems. They can also use their experience to apply advanced analytics techniques and uncover valuable insights from the data, troubleshoot issues and provide ongoing support to maintain the solution’s performance, and keep your team up to date with industry trends and best practices.
Without a knowledgeable data professional at the helm, a data management platform can become nothing more than a complex and extremely expensive database.
“Moving to a cloud-based data platform will take investment,” says Jim. “Bringing in new talent that best understands the data platform can make sure you’re getting the best out of it. Having a data professional around will also help elevate your existing team’s skills faster than theoretical training alone.”
“But hiring and keeping these in-demand data professionals can be tricky”, he adds. “One of the issues that you’ll face when bringing in new professionals who are skilled in your new data platform is that they will likely be highly specialized, expensive, and hard to retain due to the extreme competition for talent in the market. To avoid putting all your eggs in one very expensive basket, you should bring in new talent that sit at a variety of different experience levels.”
If you want to build out a project team of seven people, for example, Jim suggests using:
- 1 experienced Data Architect
- 2 or 3 mid-level Developers
- 3 or 4 internal junior Developers
“A mixed team like this will make sure that the project has the best blend of productivity, feature usage, and business knowledge, while also helping to upskill your existing talent and ensuring a healthy level of skill retention if the more senior members of the team move on.”
How to access certified data engineering talent the easy way
Hiring skilled Data Engineers for your data management team can be a real challenge. In a competitive market where demand far outstrips supply, it’s often tough to find people with the right skills without breaking the bank.
That’s why Revolent created its Data Engineer talent program. With Jim at the helm, the program takes experienced professionals and upskills them in data engineering while they earn key certifications before they are placed with clients looking at the next stage of their digital transformation.
Our program helps you find the right people for your team with zero capital investment, giving you access to certified talent who are ready to make a difference from day one. We asked the man behind the program what puts this model head and shoulders above similar schemes.
50% practical, hands-on training
“A few things set Revolent’s program apart from others,” says Jim. “The first is the course itself. About 50% of the duration is spent in hands-on labs, some of which are worked on individually, others as teams.”
Throughout their training, participants (affectionately known as Revols) are equipped with data engineering skills, official vendor certifications, and plenty of hands-on opportunities to apply their ability in real-world scenarios. “Our capstone project, for example, is an end-to-end project that the students complete in teams,” Jim explains.
Crucial soft skills
As Jim puts it, “The training doesn’t just focus on hard tech skills either. A good data engineer needs to understand different database technologies and how to interact with them, so we also teach students what kinds of people will be on a typical project team. We want to set them up for success, so we provide enough context and detail to help them communicate well with a project team when they start their work placement.”
Recruitment that finds the best fit
“Another thing that sets Revolent’s Data Engineer talent program apart from others is our Talent Acquisition team,” says Jim. Revolent handles the entire recruiting, training, onboarding, and development process for our clients’ Data Engineers, beginning by sourcing candidates with specific skills or industry experience.
“Revolent’s Talent Acquisition team not only find the best talent, but they work with our clients to find the best fit for their business, and their industry. As someone who’s worked on more than 20 teams throughout my career, I can attest to the quality of Revolent’s recruiting.”
Our Data Engineer talent program is making transformative data talent accessible to more businesses than ever—and it sounds like Jim’s having a great time too. “Everyone within Revolent is talented, fun, and committed to helping aspiring data engineers be their best. The Hire-Train-Deploy model for developing talented engineers is both a win for the engineer who wants to upskill and for Revolent’s customers who are looking for specialists.”
