Five Important Movements in the Data Analytics Landscape in 2019
by Larry Pearson
Business is booming in the data industry. Investments have grown exponentially in recent years and according to industry experts, the trend is expected to continue. As data complexity rises and more uses for data analytics take the spotlight across industries, the demand for solutions to meet these challenges is expected to surge.
We’re witnessing five up-and-coming trends that stand out as increasingly important investment areas and concerns for organizations and IT leaders.
#1 Data Quality Management (DQM)
Gartner estimates that organizations lose an average of $15 million annually due to poor data quality. That explains why enterprises are focusing on the quality and the context in which the data is being interpreted. According to a survey by Business Application Research Center, data quality management will become a key priority for organizations in 2019.
DQM involves four steps:
Implementing advanced data processes
Managing oversight data
#2 ML-based data governance
According to Gartner, organizations have started realizing that data governance is a necessity; however, they lack experience in implementing enterprise-wide governance programs with actual, tangible results. In 2019, organizations will focus more on data governance to strike a balance between data access and security. Machine learning based data preparation tools will help in governance and reinstate trust and reliability in analytics practices.
#3 More investment in hybrid cloud and AI
With businesses exploring options to shift from enterprise data warehouses to meet their demands and scale business operations, the open stack-based cloud platform is already popular. 2019 will witness increased interdependency between artificial intelligence and cloud. With many data warehouses already in the cloud, players such as AWS, Microsoft Azure, IBM Cloud, and Google Cloud Platform will expand their AI cloud portfolio to let enterprises deploy AI on the cloud.
#4 Unified view of data
With data coming in from multiple sources and in different formats at different speeds, it is becoming imperative for businesses to have control over their data. While a modern data warehouse or data lake helped enterprises bring all the data in one place, they are still struggling to offer a unified view. In 2019, two massive trends will shift the focus:
Different vendors will come together to standardize data models, leading to more consistent formats for cloud-based data sources.
Enterprises will build data catalogs, which will enable audit of the entire big data architecture. More like a centralized hub that everyone within the enterprise can access, these catalogs will link enterprise data management with analytics.
#5 Augmented analytics
As data scientists struggle with vast amounts of data to process, businesses relying on traditional machine learning platforms often miss key real-time insights. Augmented analytics, which is based on machine learning (ML) and natural language processing (NLP), can enhance data analytics, data sharing, and business intelligence. It reduces the dependency on data scientists and can also overcome the lack of business expertise that data science teams possess.
In 2019, enterprises will use AI-powered augmented analytics tools to identify data sets, develop hypotheses, and identify data patterns automatically, reducing risk and accelerating error-free modernization.
Are you ready to meet the demand in 2019?
2018 was a landmark year for big data as the industry experienced more radical changes in data storage, organization, and analysis than ever before. Organizations today are increasingly storing and processing data to derive insights and tapping into its full value. Realizing ROI from big data projects was a myth at the beginning of the big data bubble, but now we’re seeing winners emerge in this space. 2019 will see a faster increase in the number of companies, IT projects, vendors, solutions, and teams that support the work.
Simply put, the landscape is growing in ability, size, and complexity.
As the market shifts in the direction of maturity and complexity, it demands a new kind of data warehousing that is fundamental in delivering on the overall promise of big data, data insights, and ROI.
We’re already fully engaged in gleaning the possibilities of big data analytics and are continuously experiencing ongoing innovation in logical data warehousing.
We invite you to join the conversation around 2019 data warehouse trends. Contact us today.