Three major dilemmas of big data

【51CTO.com Quick Translation】 Big data, as a set of technologies and a business strategy, is relatively mature. The benefits of this maturity are more advanced tools, smoother deployment, and new business opportunities. The downside is that if companies want to be truly successful in achieving their digital transformation goals, new challenges will emerge that require smarter strategies.

A company’s digital transformation should start with a clear understanding of trends and obstacles to better chart a course toward the business outcomes it seeks. With that in mind, here are the top three data trends we’re watching, as well as the top three dilemmas that may stand between a business and success in the digital age.

Three major trends

1. Real Machine Learning
We firmly believe that machine learning and artificial intelligence will soon take over the world, at least most of the work done by humans. However, reality is advancing step by step, and we have found that machine learning can most effectively become an assistant to humans rather than a replacement. The combination of human work and machine learning is the best result.

2. From data collector to data producer
In the past, companies have been focusing on mining their own data and discovering and collecting data owned by other organizations. But now, companies need to shift their strategies and consciously create the data they need to sell new products and services and meet business goals. For example, a physical examination company collects information about patients' lifestyles and insurance company's insurance conditions, and provides personalized customer service and guidance based on this. Such companies will go further and collect and provide data in a targeted manner based on customer needs.

3. New ways to optimize customer experience
One of the most important battles in the field of big data is to improve the user experience. Judging from the current trend, using natural language processing to analyze existing data is a good way. For example, sentiment analysis on social media will make it easier to capture user likes and dislikes, thereby improving products.

Three major obstacles

1. The Dilemma of Data Processing
Data handling has always been a top concern, and the concept of data handling is a more granular control required to meet the requirements of the upcoming GDPR and other regulations. Companies not only need to control who has access to what data, but also need to know the origin of the data (chain of custody), who owns or controls it, whether the data has been modified (replaced by this data set) and other information management related to reliability, security and accountability.

2. Many cloud management mistakes
Managing and keeping track of multiple cloud environments is a fairly cumbersome task, and as more data, applications, and processing power move to the cloud, enterprises can expect this to cause some problems. While at first glance, the emergence of a multi-cloud world is not as headache-inducing as imagined, after all, it provides countless opportunities and challenges, but what we need to do is carefully consider a good way to build a cloud-managed global enterprise.

3. Barriers to self-service
Self-service is very popular today, it separates data from data and puts users in charge of it. Unfortunately, in most cases, a bottleneck appears, and the obstacle here is the scale problem - how to enable hundreds or thousands of users to use data at the same time. Separating data from IT and moving to a user self-service model is only the first step in transforming a company into a truly data-driven organization. The next one is to transform data from ordinary business to the engine of corporate profitability.

all in all
In my opinion, some big data cases are limited to our speculation and imagination, but there are some scenarios we can already see, such as the maturity of customer purchasing experience: a pair of grandparents buy a fire truck toy as a birthday gift for their 6-year-old grandson, and then receive a new product introduction, which includes recommendations for birthday gifts for children of all ages. Imagine predictive analysis, power automation to prepare for your next meeting, collect the digital documents you need to complete in advance, order lunch that meets the taste and health requirements of everyone in the meeting, and so on.

The world of big data has gradually evolved over the past four years, but the latest and most exciting part is yet to come. It is important to realize a true ROI from any big data deployment results from the processes a company sets up to leverage data and continually improve those processes and methods to become more data-driven. Focusing on the future and using the tools needed to adapt to current trends and address immediate obstacles is the best way for any company to traverse its digital transformation journey .

By Ashley Stirrup
Original link: https://dzone.com/articles/3-top-trends-in-big-data-and-3-things-holding-them
Liu Nina

[Translated by 51CTO. Please indicate the original translator and source as 51CTO.com when reprinting on partner sites]