5 Things Businesses Need to Know About Data Science
Everyone is saying Big Data is the next big thing for companies of all sizes. To understand its full potential, it is also important to become familiar with data science. Ultimately, business results do not rest solely on how much data a business has, or finding ways to create more, but on how an enterprise goes about leveraging that information, says Yacov Salomon, head of data science, Krux.
Data science, as a discipline, is a dynamic and multifaceted blending of technology, mathematics, and human insight. As companies approach Big Data and consider the role data science plays within their operations, there are five questions to consider.
1. What is the first step companies should take in employing data science?
Companies should first address specific goals and evaluate what they want to achieve with big data. Smart technologies and people are necessary to manage data, sift through, analyse, and bring what’s relevant to the surface. For some companies this means investing in the right people – building and refining integrated, in-house data science teams, and embracing a data-driven transformation. For others it might be investing in the right tools and relying on outside consultants and experts to lead the way. There is no one-size-fits-all approach.
2. Whose responsibility is it?
Data Science is a team endeavour and companies shouldn’t expect it to be managed by a single leader. Data scientists are often people with both the technical expertise of a data analyst and 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 address a specific business problem. But they can’t do this alone. An effective approach requires a diverse roster of talent, utilising a variety of skills. These skill sets may already exist within an organisation, but pulling it all together requires businesses to rethink their existing teams in ways that can support an effective data science strategy. 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 organisation.
– Privacy and security leaders who make sure it’s included at every step.
3. How will a data-driven approach change companies?
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. In addition, as data reveals new insights into areas where efficiencies can be achieved, CEOs will see emerging opportunities. That will require them to champion change and gain require broad support. These changes can include promoting continued integration and collaboration between C-suite roles, among others. Businesses with a siloed structure may face additional change as areas like technology will no longer be the sole domain of the chief information officer or IT department, but a critical component of almost every part of the organisation. Ensuring that the entire company embraces this transformation is critical to realising the power of data science.
4. What kinds of companies should be employing data science?
All companies, from a global brands to a corner markets, generate data. While not every organisation 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 analyse 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 maximising and protecting their data and using it to effectively target customers.
5. What benefits does controlling your own data bring?
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 organisations to harness information and insight they might not know they have.
Data has the potential to offer businesses a tailored competitive advantage, and can unlock new ways to use data from customers, existing infrastructure, and third parties. But if it is not understood and managed properly, it will be much harder for a business to realise that potential.
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