Five Data Trends That Will Transform Cloud And AI In 2018

Building an operating system for data is the foundation needed for any industry today. These could range from a health care organization crafting a strategy to comply with General Data Protection Regulation ( GDPR) and Health Insurance Portability and Accountability Act (HIPAA) policies, to an airline using artificial intelligence (AI) to pinpoint maintenance issues sooner and get passengers to their destinations on time.

As we move further into the new year, companies may need to harness greater amounts of their data for competition and innovation. This will not only help to solve the challenges surrounding dark data and upcoming data regulations but will also open the door to uncovering new ways to innovate with data and AI. As more organizations take hold of their data with cloud technology, we can expect these five trends to continue to change the way we view the potential of cloud and AI in 2018.

Data Preparation Will Shift To Support Data Science And Fuel AI

Previously, data scientists worked by the 80/20 rule, with 80% of their days spent finding and preparing data and just 20% on actual data analysis. Thanks to advancements over the last year in cloud-powered data cataloging and data refining, this equation has been flipped. By using technologies that can automatically ingest, classify and organize all of a company’s data sources, data scientists can now spend more time creating and exploring new models and projects with ready-to-go data sets instead of spending long hours priming them manually first.

The AI edge of companies that adopt these tools over this next year will significantly accelerate. Just as a well-prepared kitchen stocked with ingredients is critical to a successful restaurant, the rapid availability of primed data will be key to building competitive products. We should expect to see more technologies that streamline the cleansing and ingestion process to come to market, further feeding the scope and speed of AI development.

More Data, More Ways To Tap Into Higher-Value Services

We’ve seen the rapid adoption of cloud in industries such as retail, manufacturing and insurance — and according to the , over 90% of enterprises report using the cloud as part of their business. Companies see the increased efficiency and innovation potential that a solid cloud data platform offers, and now they’re beginning to tap into the data science and AI opportunities that the cloud unlocks.

2018 will be the year we see AI and data science, powered by the cloud, make their way further into a wide range of wildly different industries.

Cloud Object Storage Will Fuel An Intelligent Brain Stem For Business

With so much data coming into and flowing out of a company, organizations need a way to manage exponential data growth in a scalable, efficient way that can help them achieve new productivity in the cloud.

This is where cloud object storage – the foundational data store for cloud and AI – comes into play. As companies begin to work with larger data workloads, they will see the need for an intelligent data storage layer on the cloud that offers this kind of efficiency and high scalability. Folding cloud object storage into their architectures will allow them to manage and analyze their data economically and securely.

We can expect cloud object storage to move from an emerging technology to more of an industry standard as the size of datasets continue to grow.

Compliance Will Turn Into An Opportunity For AI

As GDPR looms over businesses that handle the personal data of EU citizens – bringing strict and hefty fines with it – we can expect compliance to become a reality in 2018.

Instead of viewing this as a draw on their operations, businesses can turn compliance into an opportunity to embrace data science and AI. Simply put, GDPR may be the forcing function for many organizations to get their data in order. Building a cloud-powered foundation for organizing and securing data will open up the door for businesses to not only fall in line with new regulations but also to start tapping into their newly organized data streams for machine learning and AI.

Overcoming The Biggest Challenge Of Cloud Migration: Culture

Often, one of the biggest challenges companies face with cloud migration is their own culture. Culture drives everything, and when a company migrates to the cloud, businesses need to determine whether their teams will embrace new ways of doing things, flourish in a climate of trust and retrain with enthusiasm.

The first step for cloud migration is to recognize where there could be cultural challenges. Many organizations with legacy applications also have legacy cultures – including walled-off information, silos and disjointed processes. Moving to more agile and collaborative ways to work will not only ready a company for migrating to the cloud but can also help lead to more well-rounded teams, increased creativity through greater data sharing, a stronger use of collaboration tools and increased trust.

As your company works toward a foundation for data and working in the cloud, be sure to keep these trends in mind. Tapping into these could unlock keys to harnessing your business’s most vital data and new ways to transform your business with it in the year ahead.


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