At its foundation, data science isn’t about creating or having more data. It’s about leveraging the information you have, and using it effectively to drive results. It’s a dynamic and multifaceted field that blends technology, mathematics, and human insight. But to be effective, data science has to be understood. Here are are some things to keep in mind.
1. Data science is not one-size-fits-all.
Organizations need to stay ahead of their data, but sometimes that can feel like an impossible task. To help, enterprises need smart technologies that allow them to sift through, analyze, and bring relevant data to the surface.
To unleash the power of data science, companies must first address their goals and evaluate what they want to achieve. Then they must explore their strategies.
For some, data science means investing in the right people – building and refining integrated, in-house data science teams and embracing a data-driven transformation.
But for other enterprises, it might mean investing in the right tools and relying on outside consultants and experts to lead the way. There is no one approach that will suit all organizations.
2. Your chief data scientist can't do it all.
Data scientists are a hybrid breed. They combine the technical expertise of a data analyst with the business acumen of an entrepreneur. They delve through disparate data sources to uncover hidden insights and recommend ways to apply that data for a competitive advantage or to address a specific business problem.
But data science is also a team endeavor and businesses cannot expect it to be managed by a single leader. An effective approach requires a diverse roster of talent, utilizing a variety of skills. Data science teams should include:
• Experts in collecting the right data, but also those who ask the questions needed to drive desired business outcomes.
• Members who can understand data and present it visually to other parts of the organization.
• An emphasis on privacy and security efforts and team members who are making sure it’s included at every step.
These skill sets may already exist within an organization, but pulling it all together requires businesses to rethink their existing teams in ways that can support an effective data science strategy.
3. A data-driven approach will change your business.
When a business takes a new approach to data, it can usher in broad cultural changes. To prepare, executives and wider teams may have to adjust to a new set of operational rules. As data reveals new insights into areas where efficiencies can be achieved, CEOs will see emerging opportunities. That means they're going to have to champion change that will require broad support.
Changes can include promoting continued integration and collaboration between C-suite roles. Businesses with a siloed structure may face additional change. Technology will no longer be the sole domain of the chief information officer or IT department, but become a critical component of almost every part of the organization.
4. Data science is not just for big business.
Every business, from a global brand to a street-corner market, generates data. While not every organization is capable of rounding up an in-house data science team, new tools are making it easier and more affordable than ever to collect and analyze information.
To tap into the power of data science, businesses are increasingly turning to “data as a service” (DaaS) solutions. For example, marketers and publishers are leveraging data management platforms (DMPs), such as Krux, to ensure they are maximizing and protecting their data and using it to effectively to target customers. While this makes deriving insight from data more cost-effective, organizations must take steps to ensure they maintain control of their data.
Data leakage — the unauthorized skimming or theft of data by third-parties — is a chief concern for digital publishers and marketers alike. If you’re leaking data, you’re also leaking revenue, whether via middlemen who use your data to create a competitive offering or via page latency, as rogue pixels increase user wait-time and slow site traffic.
5. You need to control your data.
Data brings clarity. Businesses make decisions around what’s worked in the past, industry knowledge and experience, or projected ROI.
By using data science, companies can reduce or even eliminate uncertainty. It helps organizations to harness information and insight they might not know they have.