5 Data Trends in 2018 Organizations Should Take Note

How to effectively use data to accomplish business goals and drive growth has long been on many companies’ minds, and 2018 promises to be the year more organizations shift to incorporate data into their daily workflows.

From the impending Gross Data Protection Regulation (GDPR) to the increased implementation of self-service data analytic technologies, here’s a look at 2018’s emerging data trends.

Data analysts

Increased Data Protection Efforts

Cybercrime has exploded over the last five years and doesn’t show signs of slowing down. As attacks continue to evolve and become harder to stop, developing proactive cybersecurity defense and investing in adequate data breach insurance aren’t best practices anymore; they’re critical to ensuring a business stays afloat.

The number of records breached has risen from 3.8 million in 2010 to a record-high 3.1 billion in 2016! Last year, 2017, continued the climb, with 7.9 billion records compromised. Considering that the average data breach costed organizations 3.62 million at an average of $141 per record stolen, a hefty cybersecurity policy is one of the most justified costs a business can have.

Data Governance Through the C-Suite

Do you collect and store EU customer data? If so, what’s your plan for May 25, 2018 when the GDPR officially becomes law? The fines are steep enough to cause anxiety in companies of all revenue types (up to 20 million Euros or four percent of annual global turnover depending on which is higher).

But even the prospect of those crippling fines has yet to result in compliance. Consider that two-thirds of companies aren’t sure if they’ve removed all personal information from their systems while 82 percent don’t know where their most sensitive personal data is stored.

But with those fines, meeting compliance seems inevitable for any company that wants to continue operating. Upholding GDPR compliance will give way to the emergence of a relatively new C-suite role: the chief data officer (CDO), as well as the creation of the data protection officer (DPO) for additional support.

Data is already a vital resource that often dictates the long-term fate of a company’s innovation and growth, but with the stricter measures protecting consumer data, it’ll take a dedicated CDO (and DPO working under them), to fuse data collection with business value while staying within the law. This allows the chief information officer (CIO) to focus more on the equally pressing topic of data security addressed in point one.

Data curators

Emergence of Data Curator Roles

We often hear of technology and AI eliminating human jobs, but in the case of data analytics, it’s creating them. According to Gartner, by 2022 AI will have added a net 500,000 jobs, adding 2.3 million new ones and eliminating 1.8 million old roles.

Data curators will serve as a vital conduit between data engineers and the data consumers across a business. They’ll ensure that the proper datasets are used, dictate the type of analysis suitable to various departments and strategize how to make raw data easily accessible to the employees who need data analysis to efficiently fit into their daily role.

Using Search Driven Analytics to Provide Self-Service at Scale

The ‘gather-and-store’ model not only makes data analysis inaccessible to most users of a company, it makes decision-making harder because without real-time access to data, it’s hard to form actionable insights.

Instead of manually sifting through report after report, looking for a pattern or key detail in the data to form insights, companies will adopt more user-friendly analytics tools to make data analyzation easier for all levels of the company. With search-driven analytics, the whole company has access to the data they need when they need it so daily decisions can be easily informed by data. Search-driven analytics can also be enhanced with embedded analytics, allowing companies to incorporate the software into different mediums, such as a customer or partner portal.

Predictive Analytics Improving Data Hygiene

Having a proper data foundation is a prerequisite to carrying out a successful data analytics strategy. However, no single tool or employee can save a company from becoming entangled in their own data. Machine learning models like predictive analytics will continue to gain steam, particularly in the area of detecting data-quality anomalies. Instead of an employee manually discovering a particular tracking hasn’t been working right for months, predictive modeling will safeguard against analytic problems flying under the radar.

Data gathering will continue to be game-changer it’s been for decades, but with a fast-moving digital world and future regulations inspired from the GDPR, these trends will be critical to business’ success and growth moving forward.