Data is the fuel that drives the engine of today’s businesses. Every process and workflow is aided by insights gleaned from data, which becomes increasingly available with each passing day. Now that the Internet of Things is upon us, it’s possible to collect data on anything and everything — and we can only expect this trend to grow.
The true value of data is how it reveals information that might otherwise be invisible. These revelations, in turn, help propel growth, spark innovation, and give companies advantages over their competition. As a result, at least some familiarity with data science has become essential for aspiring executives.
Business leaders must provide direction and guidance to their teams. Fortunately, this high-level decision-making is much easier when it’s informed by objective facts and empirical figures. Executives who can understand, manipulate, and analyze data are in the best position to achieve results.
Look no further than Richard Hopkins, the national lead of PricewaterhouseCoopers’ specialist improvement team in Australia. Richard is a great example of an analytical executive, combining top-down consultant insights with bottom-up data knowledge to achieve a complete picture of business operations. As a result, he’s able to identify issues and achieve solutions in a fraction of the time it might take others.
What executive wouldn’t want to follow suit? The world is increasingly powered by data, so it’s an ideal time to gain expertise in data science.
Preparing for Data Science Success
Data science offers a tremendous opportunity, but it’s only available for individuals who are eager enough to seize the moment. Executives who are serious about adding data science to their skill sets must be driven and directed.
Working executives who want to gain data science skills must also be strategic about where and how they get their information. There is a lot to learn, and the average CEO must first figure out how to extract the proper insights from data.
They must also be able to think outside the box, as some of the more complex problems of the data world require abstract solutions. Once executives understand what their data is telling them, they can begin to make informed decisions.
The key to developing a baseline understanding of data science is to focus on the skills that are relevant right now. Here are a few data science trends to watch in 2018:
- Artificial intelligence and machine learning: Analytics is only an advantage if it’s easy and accessible. In response to the flood of data coming from IoT devices, companies are using automated technologies to streamline collection, storage, analysis, and more. AI is already an integral part of the user experience on top sites such as Amazon, Google, and Facebook, with an army of startups racing to push the technology ahead. Executives who learn how to apply AI properly can help increase the productivity and efficiency of their organizations.
- Big data in the cloud: The scope of big data has always been an issue, and the cloud is the natural solution. The four cloud computing giants — Amazon, IBM, Google, and Microsoft — are developing data management services native to the cloud. These services will be central to how companies ingest and process data in the future, which means executives must understand the benefits and hazards of the cloud. The success of companies in 2018 and beyond will be intimately linked to the success of cloud-based services.
- The Internet of Things: This is simply another term for connected devices. Anything that is able to transmit data over a network, whether it be a fitness tracker or a piece of heavy machinery, falls into this category. IoT devices will be a significant data source moving forward, which means companies must prioritize the implementation and management of these devices. Executives who pursue an effective IoT strategy will be able to work with data that is incredibly comprehensive and unique.
- Open-source software: Some of the most promising data-management applications are being built using an open-source development model. Rather than being exclusive or proprietary, open-source code is available for anyone to improve and amplify. Companies that make the most of open-source software are able to reduce technology costs while building a strong foundation for data-driven initiatives.
- Unstructured data: This concept refers to information that is important but not formalized. Think of emails, social media posts, or the results of open-ended surveys. Advanced analytics is able to incorporate this data to produce deeper and more accurate insights. Executives who find ways to capture and incorporate additional unstructured data can give a shot in the arm to their analytics initiatives.
In addition to the technical aspects of data science, one of the most important parts of this trend is learning how to convey your knowledge. Data is massively complex and comprehensive, which makes it difficult even for experts to understand. Extracting insights is the first step, but the crucial follow-up is finding ways to communicate and contextualize those insights so they’re accessible to all. Executives need to develop tech skills, but they can’t lose sight of their duty to educate and inspire.
With data science becoming increasingly mainstream, there’s a clear need to make it a more integral part of the corporate world. Data must be involved in as many decisions as possible, and it’s going to become crucial that executives have a baseline understanding of the field. To make the most of the growing volume and quality of data, business leaders must invest time now to get ahead of the trend.
Check out the SuperDataScience Podcast to stay up-to-date on the latest developments in the field, week in and week out.
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Author: Kirill Eremenko