The effective use of data to achieve business goals and drive growth has long been in the minds of many companies, and 2018 promises to be the year when more and more more and more companies are adopting the data in their daily workflows.
From the impending Raw Data Protection (GDPR) regulation to the increased implementation of self-service data analysis technologies, here is an overview of emerging trends in the 2018 data.
Increased data protection efforts
Cybercrime has exploded in the last five years and shows no signs of slowing down. As attacks continue to evolve and become more difficult to stop, the development of a proactive cybersecurity defense and investment in insurance against adequate data breaches is no longer a best practice ; they are essential to make sure that a business stays afloat.
The number of pirated recordings rose from 3.8 million in 2010 to a record 3.1 billion in 2016! Last year, 2017, continued the rise, with 7.9 billion records compromised. Considering that the average data breach cost organizations $ 3.62 to an average of $ 141 per stolen record, a hefty cybersecurity policy is one of the most justified costs that a company can have.
Governance of Data Through C Suite
Collect and store EU customer data? If so, what is your plan for May 25, 2018, when will the GDPR officially become law? The fines are stiff enough to cause anxiety in businesses of all types of income (up to 20 million euros or 4% of the annual global business figure according to what is The highest).
But even the prospect of these crippling fines has not yet resulted in compliance. Consider that two-thirds of companies are not sure if they have removed all personal information from their systems while 82% do not know where their most sensitive personal data is stored.
But with these fines, compliance seems inevitable for any company that wants to continue operating. Maintaining compliance with the GDPR will give way to the emergence of a relatively new role in management positions: the Data Manager (CDO), as well as the creation of the protection officer Data (DPO).
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 will take a Dedicated CDO (and DPO working under them) collecting data with commercial value while remaining in legality. This allows the Chief Information Officer (CIO) to focus more on the equally pressing topic of data security discussed in 1.
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Emergence of Data Retention Roles
We often hear about technology and artificial intelligence eliminating human tasks, but in the case of data analysis, it is the creation of these. According to Gartner, by 2022, AI will have added 500,000 net jobs, adding 2.3 million new jobs and eliminating 1.8 million old roles.
Data preservatives will serve as a vital link between data engineers and data consumers of a company. They will ensure that the appropriate data sets are used, dictate the type of analysis appropriate to the different departments, and develop strategies to make the raw data easily accessible to employees who need a data analysis. data to integrate effectively into their daily role.
Using Research-Driven Analysis to Provide Self-Service on a Scale
The "collect and store" model not only makes data analysis inaccessible to most users of a business, but also makes decision making more difficult because without real-time access to data it is difficult to form exploitable information.
Rather than sifting through a report after another, looking for a pattern or key detail in the data, companies will adopt more user-friendly analysis tools to facilitate analysis of the data. data at all levels of the company. Through research-based analysis, the entire company has access to the data it needs when it needs it, so that day-to-day decisions can be easily informed by data. Search-based analytics can also be enriched with built-in analytics, allowing companies to integrate the software into different media, such as a customer or partner portal.
Predictive Analysis Improves Data Hygiene
Having a proper database is a prerequisite for the success of a data analysis strategy. However, no tool or employee can prevent a company from getting into its own data. Auto-learning models such as predictive analytics will continue to gain ground, particularly in the area of detecting data quality anomalies. Instead of an employee manually discovering that a particular tracking has not been working properly for months, predictive modeling protects against the analytic problems that fly over the radar.
Data collection will continue to be a game changer for decades, but with a rapidly changing digital world and future GDPR-inspired regulations, these trends will be critical to business success and growth.