In this podcast, Jason Foster speaks to James Lupton, CTO at Cynozure, about major trends to look out for in data.
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There are many new trends emerging in the field of data, but it is important to realise that some trends are temporary while others will eventually become mainstream.
[00:48] James’ journey in data and how he became the CTO of Cynozure
[02:20] Major data industry trends
[02:30] Niching down
[09:10] Semantic layers
[18:15] Active metadata
[23:20] Reverse ETL
[27:30] The need for regular consolidation
[29:00] Who is driving the innovation
[35:20] Creating adaptability through a more modular mindset
[38:40] Some trends which may have run their course
As data has become more commonplace in organisations, systems and software have been created to address the majority of data needs. The core functionality of most data platforms (such as collection, storage and access) is now dominated by a number of key players and architectural patterns. As organisations mature beyond the basics and look to improve their platforms, they will increasingly turn to niche vendors and niche solutions that focus on specific aspects of the value chain. The trend towards specialisation will only continue as technology advances, so those who cater for these specific niches will be in high demand.
With the massive amounts of data being collected by businesses every day, it is more important than ever to find a way to organise and use that data effectively. With the explosion of tools and data consumption the last few years has seen, there has been a corresponding increase in the challenges around data management, especially ensuring consistent definitions of data across the business. Enter the metric layer. This new approach to consolidating the access to key metrics into a single, consistent location is shaping up to become one of the defining features of the next iteration of the modern data platform. It’s still early days, but it’s seeing big investment from key players in the market so watch this space.
Metadata has long been understood to be key to managing a successful data platform, but that metadata is usually collected and then stored somewhere, waiting to be accessed when needed. A new breed of metadata management tools is now emerging that focuses on active metadata – think it of it as metadata driven automation. Instead of waiting for human review and intervention, active metadata aims to drive proactive, automation driven data management approaches whether that is acting on a data quality score or dealing with new sensitive data that has arrived in the platform.
As data continues to grow in importance, businesses will need to find new and innovative ways to extract insights from it. This is where data innovation comes in – it’s the driving force behind breakthroughs in data-driven strategies and decision making.
While it’s easy to think that innovation is being driven by the vendors, in many ways they are reacting and creating solutions for problems that have evolved in end user organisations. In particular, a general trend towards decentralisation appears to lie at the heart of many recent trends.
Still, there is no one factor that dominates data innovation. Rather, it is a complex mix of technology, business needs, and user demands that shapes how data evolves. While big companies like Google and Facebook tend to get the most attention for their innovations in data, they are not the only ones shaping its future. Small companies, startups, and individual developers are also playing a role in driving data innovation forward.
Innovation in data is crucial for businesses to stay ahead of the competition. However, not all data trends are permanent. It’s important for businesses to analyse and study different data trends before implementing them into their strategy. By doing so, they can create a long-term plan that will be successful well into the future.