As more companies leverage Snowflake's cloud data platform for data analytics, operations, and product development, it's more important than ever to have the right team to help with data strategy, data architecture, and execution.
In-house talent is always ideal, but there are scenarios where it can make sense to hire a data consultant.
When standing up a business intelligence function, building out a data science organization, or offering data solutions as products to your clients, it's worth considering a data consultant.
One of the clearest reasons to leverage Snowflake for data warehousing is to transition your company from subjective decision-making to data-driven decision-making.
Because most companies are brand new to data, it's common to start from the beginning.
How does Snowflake work?
What business value do you plan to create?
Are there specific Snowflake solutions that make the most sense?
Without prior expertise in cloud data warehouses or Snowflake implementation, I've seen many companies hire unqualified talent, purchase the wrong technologies for their workloads, or take too long to build a solution.
Portable does not offer consulting services, but I still recommend considering them in almost all scenarios.
Most data consultants have pricing that works on a project basis, an hourly basis, or via a retainer model.
Unless you are signing up for multi-million dollar massive engagements, it's typical to have contracts that last one month, a few months, or at most a year.
While a consulting partner can be more expensive than hiring your team of data analysts, data engineers, or data scientists, these companies have deep expertise in standing up the right technologies, quickly, to create business value.
So what types of solutions do Snowflake data consultants offer?
There are a handful of common scenarios where a services partner can help you with your data initiatives. It's common for companies to offer solutions around:
2) Augmenting your in-house headcount
3) Building and maintaining data pipelines
4) Developing dashboards
5) Implementing advanced analytics
6) Mitigating cloud costs
Let's do a deep dive into each use case.
Consultants can help you create a business value strategy, help with the foundational decisions you'll make when standing up your data stack (like which cloud provider to pick - AWS, Azure, GCP), explaining which capabilities to be aware of (data sharing, streaming inserts, etc.), and outlining the vocabulary and technology partner landscape for you to traverse the ecosystem effectively.
Once you have a strategy in place, you need a team to execute the plan. Services partners have ample talent on-hand, ready to help with existing projects or to jumpstart new data initiatives quickly. Two scenarios where it can make sense to leverage a consulting solution instead of in-house resources are:
Standing up a technology stack - Where expertise in architecture, the landscape, and the pros and cons of different technologies are quite valuable
Competitive job markets - If you need resources quickly to execute an ambitious strategy, it can make sense to leverage a consultant to get boots on the ground faster than hiring in-house
In both scenarios, you can always hire in-house talent over time, but getting started quickly is critical with all data projects.
Once you have put in place the strategy, the business outcomes, and the team, it's common to then start processing data.
This is where ETL / ELT pipelines, SQL data modeling, python processing, and infrastructure deployments (likely cloud deployments, but also on-premises) can come into play.
Regardless of the pipeline you are building, it's important to have the right architecture in place - ensuring scalability, speed, and observability are built into your big data pipeline to help your team sleep well at night while data moves.
Now that you are processing data, someone needs to build dashboards, create reports, and expose insights to your internal stakeholders.
A quick Google search will show you that there are entire consulting firms focused on data visualization. Even more specifically, there are entire consulting firms focused on building visualizations with specific tools - Power BI, Tableau, Looker, etc.
When considering the best approach, it's important to not only consider the technologies but also to understand your specific industry or vertical. For instance, if you work in healthcare, life sciences, e-commerce, or financial services, it can make sense to bring in talent (whether it's in-house or consulting talent) with direct experience building visualizations in your market.
Most companies don't need advanced analytics. Machine learning, artificial intelligence, real-time data processing, and building warehouse native apps aren't necessary for 90% of scenarios.
But if you do need advanced analytics, finding the right expertise is more important than ever. Tapping into a services partner can help accelerate the entire lifecycle of your project.
They've been there before. Why not tap into their knowledge?
Once everything is up and running, there is always room for optimization.
As you develop more dashboards, process more data, and implement more technologies, it is common for cloud costs to increase rapidly.
Data warehouses like Snowflake charge based on a combination of compute and storage costs. If you don't have the in-house expertise to optimize your data pipelines to minimize costs, hiring a consultant for a one-off evaluation can be one of the clearest ROI decisions you can make as a business.
In these scenarios, it's not uncommon to be able to pay a consultant only a portion of the savings they can generate. When your cloud bills reach a certain level, using a FinOps consultant is an easy decision.
Lucky for you, we've pulled together a list of 175+ data consultants.
If you're a small company, I'd recommend a small consulting firm.
The list includes some of the largest data consultancies in the world, as well as one-person consulting firms like The Seattle Data Guy.
If you work at a large enterprise where you need to bring in an entire team of data scientists, or you need niche expertise, it can be worthwhile to speak with a larger consulting firm that better aligns with your needs.
At Portable, we are not a consulting firm, but we specialize in building no-code ETL pipelines on-demand for clients.
Development is free, support is hands-on, and you can start moving data in minutes. No credit card required.