A company's digital transformation should start with clear trends and obstacles to better chart a course to the business outcomes it seeks. With that in mind, here are the top three data trends we're focusing on, as well as the top three dilemmas that can come between a business and success in the digital age.

The Three Big Trends

1. Real Machine Learning

We firmly believe that machine learning, artificial intelligence, will soon take over the world in the future, or at least most of the jobs of humans. However the reality is advancing on us step by step, and we are finding that machine learning can most effectively be an assistant to humans rather than a replacement. The combination of human work and machine learning is the best outcome.

2. From Data Collector to Data Producer

In the past, organizations have been focused on mining the data they own and discovering and collecting data owned by other organizations. But now, organizations need to make some strategic shifts to consciously create the data they need to sell new products and services and meet business goals. An example would be a medical screening company that collects information about a patient's lifestyle and insurance company's conditions of coverage and uses it to provide personalized customer service and guidance. Such a company would go much further, collecting and providing data in a targeted way to meet the needs of its customers.

3. New ways to optimize the customer experience

One of the last few battles to be fought in the big data space will be to improve the physical user experience. Given current trends, analyzing existing data using natural language processing is a good way to do this, and sentiment analysis on social media, for example, makes it easier to capture user likes and dislikes, which can lead to product improvements.

Three major hurdles

1. The data processing dilemma

Data processing has always been a major concern, with the concept of data processing being a more granular level of control to meet the requirements of the upcoming GDPR regulations and others. Companies not only need to control who has access to what data, but also need to know where the data came from (chain of custody), who is owning or controlling it, whether the data has been altered, (superseded by that dataset), and other information related to the management of the data for reliability, security, and accountability.

2. Cloud management blunders abound

Managing and keeping track of multiple cloud environments can be quite a task, and as more data, applications, and processing power move to the cloud, organizations can tell that this will cause some problems. While at first glance, the emergence of a multi-cloud world is less of a headache than one might think - after all, it offers a myriad of opportunities and challenges - what we need to do is think carefully about a good way to build a cloud-managed global enterprise.

3. The self-service hurdle

Self-service is very popular today, separating the data from the data and putting the user in charge of it. Unfortunately, in most cases, a bottleneck arises, and the obstacle here is scale - how to make data available to hundreds or thousands of users at the same time. Separating data from IT and moving it into a user self-service model is just the first step in transforming a company into a truly data-driven organization. The next one is transforming data from ordinary business to an engine of corporate profitability.

Some examples of big data are limited to our speculation and imagination, but there are scenarios that we can already see, such as the maturation of the development of the customer buying experience: a pair of grandparents buying a fire truck toy for their 6-year-old grandson's birthday, and then receiving a new product pitch that includes recommendations for birthday gifts for children of all ages. Imagine predictive analytics, power automation to prepare for your next meeting, gathering the digital files you need to complete ahead of time, ordering lunches that meet the tastes and health requirements of everyone at the meeting, and more.

The world of big data has evolved over the past four years, but the best and most exciting parts are yet to come. It's important to realize a real ROI from any big data deployment as a result of the processes set up by a company to leverage data to continually improve those processes and methods to become more data-driven. Focusing on the future and using tools that can adapt to current trends and address the immediate obstacles needed is the best way for any company to traverse the digital transformation journey .