“ We have also developed a unique solution that addresses common pitfalls such as missing observability , quality , reliability etc . when it comes to managing data sprawls across multiple data platforms ”
“ We have also developed a unique solution that addresses common pitfalls such as missing observability , quality , reliability etc . when it comes to managing data sprawls across multiple data platforms ”
issues . Clients are really looking for observability around data and what It means in the data workflow – and how that workflow supports the last mile through the supply chain to deliver sustainable analytics with clear business realisation outcomes from design thinking .
Extracting the value of data and driving actionable insights is challenging and complex . Organisations must deal with
1 YR 10 MTH
Time at Kyndryl legacy systems that have data silos and excruciating data extraction challenges . There are undefined workflows that are in unorganised data swamps across applications and infrastructure that are time consuming and with limited visibility . Sporadic data assets impair the decision process for support and automation . Poor supply chain across many persons causes ‘ garbage in garbage out ’ throughput and is the cause of many failed AI programs .
It doesn ’ t take a village to achieve a successful program , but it does require attention to the right mix of technology and business resources . Because of these challenges , organisations face headwinds across their skills and resources and their ability to provide strategic direction and intent to the program . There is a vacuum of tribal knowledge
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