Modern data pipelines have become more business-critical than ever. Every company today is a data company, looking to leverage data analytics as a competitive advantage. But the complexity of the modern data stack imposes some significant challenges that are hindering organizations from realizing their goals and realizing the value of data.
Cloud complexity is an inevitability. Regardless of where an organization may be on their cloud journey – on-prem, in the public cloud, or managing an expanding hybrid cloud – the reality is managing the enterprise isn’t getting any easier. Demand continues to rise for greater access to more data across the organization to do things like run analytics and machine learning and to automate more processes.
We all make daily decisions with the help of AI, perhaps without even realizing it. Advanced automation technologies using data from smart devices and social networks make it easier than ever to offload your decision-making to an algorithm. Recommended posts, ads, suggested products — none of this is possible without automation. But machines can only get us 90% there. They’re great at consuming and analyzing large volumes of data, but still have trouble with edge cases.
In the ever-expanding world of IoT, no industry is left untouched and the growth potential shows no sign of slowing down. According to a report published by GlobalData in May 2021, the global Internet of Things market is expected to reach more than a trillion dollars by 2024. Predictive maintenance, optimized energy consumption, road traffic management – the use cases are virtually endless! Meanwhile, that connectivity is generating a goldmine of data for your business.
With data becoming a more important business resource by the day, organizations are increasingly turning to their leaders to ensure data excellence. Mark Fazackerley, Regional Vice President ANZ at Talend, outlines how the growingly popular Chief Data Officer role can help lay the groundwork for an effective data strategy and culture.
Firms are burdened with tech debt and endless regulatory compliance, often leaving innovation last to receive the necessary budgets. Data-fuelled innovation requires a pragmatic strategy. This blog lays out some steps to help you incrementally advance efforts to be a more data-driven, customer-centric organization.
