As the availability and complexity of data, data sets, and data sources grow, we can’t lose sight of finding and leveraging new insights that are actionable and meaningful for our customers and our own organizations. Companies that are unable to keep pace with the volume of data growth will get left behind. That’s why we’re accelerating our data science growth, investing in key technology and training partnerships to upskill and arm our employees with the capabilities they need to support our clients' most pressing challenges for years to come.
Traditionally, data scientists are thought of
Now, we’re taking yet another critical step in our journey – formalizing this process not just for us, but the entire industry, including our wide variety of clients. Booz Allen has joined General Assembly’s Data Science Standards Board
Our industry collaboration will take the guesswork out of the equation of determining the skills behind a data scientist. With these new standards, and aligned
We’re already seeing impacts from pilot programs we’ve rolled out with General Assembly. Our data scientists are bringing what they learn immediately back to serve our clients better:
“A Booz Allen associate who supports National Parks Service is already transforming how his team delivers to their client. He’s set up a data science function on his team and moving a lot of their analysis on larger data sets to Python and SQL as a direct result of the training, providing quicker turnaround times and increased data processing efficiency.”
We continue to invest in data science because the opportunities to gather insights from data are endless and have a profound impact. We’ve seen an airline client use data science to revolutionize their networking operations; we’ve been there to support the US Census Bureau in becoming a mathematically-driven corporation, with a data science strategy expected to save $5 billion dollars on Census 2020 operations. We’ve also seen a recent health client use data science solutions to make quicker and more accurate patient diagnoses that save lives.
Now is the opportunity for us to take a stand and embrace this effort as we move forward in standardizing and scaling data science.