Emerging Big Data Trends Redefining Business Operations

The key to answering the rising concerns about the future of effective data management and BI lies in the emerging trends in Big Data.

FREMONT, CA:The percentage of businesses investing in digital transformation today is experiencing slow growth. However, the percentage of businesses in more advanced stages of transformation is increasing. They are using more data-producing tools, sharing data with more end users, and making more concerted efforts to collect data. This raises concerns about the future effectiveness of data management and business intelligence. Various predictions will help business leaders anticipate the answers to these questions in the coming years.

Data-Producing Tools Become Diverse

The number of SaaS tools available and the volume of data they collectively produce will continue to grow. Companies are embracing more tools every year, and there is no evident end in sight. However, one not-so-obvious side effect of this is the shortening of the average customer's lifetime with these tools.

Organisations waste huge amounts of tools that are rarely used. They constantly try new ones while at the same time forgetting about others. Moreover, many of these tools are adopted at the departmental, team, and employee levels, making large enterprises and small organisations unaware of about half of their deployed SaaS tool. To counteract the pile-up of unused tools, there is increased consolidation and purging by the IT department. This, along with elevated adoption, will result in shortened life cycles for most SaaS tools. The exception will be tools necessary for company infrastructure, such as CRMs and data integration tools.

Data Integration Becomes Architecture-Agnostics

Today, most businesses use separate platforms for ETL or ELT, reverse ETL, and sometimes data replication. This is evident because while ETL/ELT and data replication are well-established processes in the data integration world, reverse ETL is a new process that is offered by a few special vendors. Reverse ETL is the final piece of modern data architecture, so firms interested in it have established relationships with vendors of ETL/ELT and data replication solutions. Therefore, it may seem natural to seek a separate platform exclusively for reverse ETL.

Over time, data integration will become such a core aspect of business that companies will stop perceiving the differences between integration processes. The tools for integration will become more user-friendly, and users will not think about the type of engineering connecting data sources with data destinations. They will demand one architecture-agnostic platform that serves all integration types, including picking a source, destination, and sending.

The race to achieve digital transformation is an extremely dynamic one. However, one way to stay ahead of the curve is to keenly observe the emerging trends in data management and BI. They provide a better understanding of innovations and advancements around the corner and help inform the strategies currently implemented.