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Data August 17, 2021
Even though data can provide a wealth of information about a business, using it effectively can be challenging. Unless you have the right skills, it can be a messy, overwhelming task.
A good analogy is driving down an unfamiliar road. If you haven’t driven along that road before, you might miss the clues that point out when you’re heading in the wrong direction. If you aren’t sure which way to go, it might take you some time to figure it out.
But a data scientist is like a map app. They know where each road leads. They know what signs to look for and why, which means you can finally avoid all the second-guessing, mistakes, and wasted time.
Of course, data scientists aren’t right for everyone. There are many situations in which hiring one might actually make things worse. So, how can you tell if you should hire a data science consultant?
To help you figure this all out, we’ve put together this quick rundown to get you started. All in all, there are five instances where hiring a data science consulting firm is better than handling the data on your own.
Data scientists earn anywhere between $92k and $138k nationwide. As of 2020, the average annual salary is $119,130, up from $94k in 2018.
This average salary indicates a high demand for data scientists, though there aren’t as many as one might imagine. It’s a highly specialized job in a competitive market. Data scientists must be literate in programming languages, algorithms, NLP, and statistics. Things like Python, SQL, Hadoop SPARK, and machine learning are just basic, expected skills in the field.
If you were to build your own team, you’d need a Chief Data Officer, data analyst, business analyst, data scientist, data architect, and a data engineer, at least.
Not many businesses can afford such an expensive, highly-specialized team. But you might need to hire professionals to handle the data-related problems you simply don’t have the skills to solve.
So what’s the best course of action? Opt for data science consultants rather than building an expensive team.
Unless you have unique data, the chances are high that previous consultants have handled similar information. This can come in handy since having prior experience can speed up project progress.
It’s extra helpful when you realize that proprietary data is tricky. When businesses deal in proprietary data, they’re essentially asking consultants to work within the proprietary programming language.
When you consider that old technology has no relevance to any other industry or company, you can quickly see how this can be a problem. For data scientists, learning these programs and languages is a career dead end, and for businesses, it’s a hassle to find the right candidate.
A mass-market solution can be useful. Most of them come with plugins that allow you to customize them to your heart’s content.
Also, SaaS solutions feature tons of self-service support, including active communities and resources that assist your team in optimizing their software. Some key challenges, such as integrating the software with other elements of your technology stack, can be solved by reading these articles and Q&A boards.
However, companies sometimes face needs that are beyond the scope of commercial solutions. For instance, with mass-market software, customization isn’t always possible. Even if it is, the cost could be quite high if you have to request a feature.
By working with consulting companies, businesses can build customized products and minimize or eliminate the risk of costly customization projects. A data science consultant may be of value if you’ve looked at mass-market solutions for your use case and couldn’t find one that met your needs.
Due to data privacy regulations, sharing data with third parties is difficult, so companies rely on synthetic data generation and data masking. It allows them to share their data while keeping it all secure.
However, it’s still a hassle to deal with, so if your project doesn’t contain sensitive data, to begin with, you’ll probably have an easier time working with data science consultants.
Typically, proprietary data is protected by copyright laws or patents. A non-disclosure agreement is often part of the contract with anyone working with the information, so data scientists are bound not to disclose any findings.
Sometimes, companies need professional guidance on strategy and implementation ― even if they’re not specialized in the market. In fact, consulting firms continue to be in high demand due to this very reason. Despite their expertise in their markets, most businesses have limited knowledge of strategy and implementation.
Consultants can make recommendations on how to implement data science initiatives in business processes. In addition to market research and surveys, they carry out cost studies, feasibility studies, and cost-benefit analyses.
So, you might want to consider a data science consulting team if you want to get some special expertise or better information. You can rely on them to provide all the information your company needs to solve burning problems and to save you time.
While data science usually requires a large investment, the benefits will often justify the costs. Still, deciding whether to move forward isn’t always easy. Some companies may not be ready to work with data scientists.
For instance, if you’re looking at data science consulting as a way to fix something, then your business may not be ready. Data science works best at improving processes already in place. So if your business organization and processes aren’t as effective as they should be, you’re almost guaranteed to see fewer benefits.
A data science consulting company might be your next big step if your business runs like a finely tuned machine and you want to boost your competitive edge.
If you’re interested in a more in-depth look at the ins and outs of data science, check out our article here.
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