Developing Your Own Big Data Infrastructure and Ecosystem for the Future
Wed, April 21, 2021

Developing Your Own Big Data Infrastructure and Ecosystem for the Future

As big data analytics and AI are becoming more prominent, the effect they will have on your infrastructure will grow as well, said Brian J. Dooley of TDWI, an online resource on anything related to data / Photo by: metamorworks via Shutterstock

 

As big data analytics and AI are becoming more prominent, the effect they will have on your infrastructure will grow as well, said Brian J. Dooley of TDWI, an online resource on anything related to data. Large volumes of data push the limits of current infrastructure— from storage to networking and security. “Big data infrastructures are multifaceted,” as noted by David Howell of technology and business news portal Silicon. By removing data siloes and integrating them into datasets, they open up a range of new possibilities that have been previously hidden from view. 

The traditional approach in managing data sets is to create layers within the big data infrastructure. But now, the cloud has dominated the way businesses tackle data management issues. This is likely to become more significant as companies modernize their big data ecosystems. Such ecosystems in the digital world offer businesses with new, expandable scalable systems. 

Combining Advanced Technologies 

Modern big data ecosystems utilize advanced technologies, particularly AI. Thanks to new analytical platforms, leveraging systems like machine learning can harness the value of big data. But ecosystems can bring much more to the table than just better data analysis. For example, big data ecosystems must be flexible, integrated, and secure as consumers use several parallel channels when purchasing goods. 

Management firm McKinsey said, “Ecosystem relationships are making it possible to better meet rising customer expectations.” The advent of mobile internet, advanced analytics, and AI have caused customers to expect fully personalized solutions delivered to them in milliseconds. Ecosystem orchestrators utilize data to connect all potential producers with potential customers and to anticipate the needs of customers before they are raised.   

Group Head of Big Data and AI for Vodafone Business David Gonzalez told Silicon said that the big data boom has prompted many industries to use data analytics. “The real value will be drawn from the intelligence it offers, especially at scale,” he said. The main characteristics of big data ecosystems are on-prem or in the cloud and in secure data lakes in which all data sources and structures are stores. The processes in delivering valuable insights “tend to be fully automated” for the purpose of bolstering speed and efficiency, thereby delivering AI at scale. 

As the data landscape becomes more complex, businesses that are capable of developing infrastructures to manage volumes of data sets will gain a competitive advantage. These data environments must be developed strategically. Enhancing the abilities of the workforce, supporting the customer experience, and transforming IT spaces are all possible when big data is integrated within a clear development roadmap. 

Modern big data ecosystems utilize advanced technologies, particularly AI. Thanks to new analytical platforms, leveraging systems like machine learning can harness the value of big data / Photo by: Rawpixel.com via Shutterstock

 

Possible Constraints on Creating Big Data Infrastructures

Jim D'Arezzo, CEO of Condusiv Technologies, said that AI and machine learning pose unique challenges to businesses. He explained that AI requires massive amounts of data, computing, power, and I/O (input/output) to develop a proper AI solution. It also needs quick access to “sufficient compute resources,” as it has an intensive I/O. Companies can benefit from machine learning by capturing “varying types of information from disparate systems” and normalizing them, explained Mark Gaydos, chief marketing officer of Nlyte Software. Organizations need to feed that data into a machine learning system and analyze the information to put analytics into action. 

CEO of Aptum Susan Bowen stated that budget constraints are a challenge for enterprises. As businesses gather more data, they need to invest in “more infrastructure to facilitate this expansion.” However, scalability demands can be met and costs can be drastically reduced by outsourcing to hyper-scalers via SaaS solutions. 

Browen explained that security is also a priority of CTO and CIO’s scaling strategies considering that more devices and users have access to ecosystems. However, the challenge here lies in managing different access and endpoints and audit control. Hyper-scalers are secure platforms but formulating an effective security strategy relies on the business’s ability to “reflect upon its vulnerabilities.” Matt Yonkovit, Chief Experience Officer of Percona, told Silicon that CIOs and CTOs avoid settling for one provider. 

Multi-cloud has yet to be put into practice for most enterprises outside. It will develop as more people become more proficient with using more than one cloud platform. Yonkovit said, “Multi-Database environments are the norm but, getting them to “share” data between them is a challenge.”

Decentralization of Data Storage

Big data infrastructures will embrace 5G and cloud computing. The era of centralized data stores is over. Decentralized information at the edge of a 5G-powered network will help create an ecosystem for big data to thrive in. 

David Gonzalez explained that organizations are also worried about managing their expectations on timing. Big data projects take months (or a year) to complete. Hence, it is essential for companies to articulate these timeframes, aligning them with the business to prioritize high-value cases, Gonzalez advised. He added, “Key processes, such as data ingestion from multiple sources, must be built fully automated and scalable.” Moreover, data governance and data quality must underscore all processes. Clearly documenting all data is also key in thriving in a data-centric world. 

Overall, big data ecosystems are complex and multifaceted, combining emerging technologies to optimize workforce productivity or forge stronger relationships with customers. Developing a modern big data infrastructure should be part of a business’s strategy. Enterprises who create a secure and robust data environment will gain a significant advantage over their competitors.