Internet of Things
AI report they experienced “a 74-day shorter breach lifecycle and saved an average of $3 million (USD) more than those without.” However, AI and machine-learning (ML) models used in cyberattack prevention products vary tremendously in their maturity and ease of use.
If you are considering adding an AI-enabled cybersecurity solution to protect a production environment, such as your factory floor, here are some questions you may want to ask:
Can the solution detect and prevent malicious attacks before they have a chance to deploy in the network - with no human intervention or internet connection required?
Will the solution have a measurable performance impact on your operational technology?
Does the vendor offer on-prem, hybrid and cloud-native deployment models? This affects whether the solution can enable modernisation efforts as your company evolves, without the need to “rip and replace.”
How many legacy operating systems in your environment does the solution support?
Does the solution require regular signature updates that might disrupt production?
The Make UK and BlackBerry study found that nearly one-third of IT leaders surveyed responded that “vulnerability to cyberattack (real or perceived) inhibits my company from investing in technological advances through interconnectivity.”
Whether your operational technology systems are air-gapped, connected, or somewhere in between, now is the time to reduce the risk of a cyberattack that can disrupt your production and competitive standing. It will free your organisation to fully embrace further digitalisation when the timing is right - and to do so securely.
BlackBerry
www.blackberry.com
nowflake has launched the Manufacturing Data Cloud, which enables companies in automotive, technology, energy, and industrial sectors to unlock the value of their critical siloed industrial data by leveraging Snowflake’s data platform, Snowflake- and partner- delivered solutions, and industry-specific datasets. The Manufacturing Data Cloud empowers manufacturers to collaborate with partners, suppliers, and customers in a secure and scalable way, driving greater agility and visibility across the entire value chain. With Snowflake’s Manufacturing Data Cloud, organisations can build a data foundation for their business, improve supply chain performance, and power smart manufacturing initiatives in today's digital-industrial world. Manufacturers face an increasingly complex and competitive landscape, where supply chain performance and factory efficiency are critical to success. Fragility has been exposed in supply chains and digitisation continues to be a massive opportunity to drive visibility into the supply chain and factory floor. As manufacturers look to address these issues, their efforts around modernisation and resiliency require data and a willingness to embrace industry 4.0 initiatives, in which data is collected from sensor networks and smart machines and filtered through artificial intelligence (AI) and machine learning (ML). Traditionally, these data sets, which encompass both operational technology (OT) and information technology (IT) data, have been siloed and difficult to access and integrate.
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The Snowflake Manufacturing Data Cloud enables manufacturers to address these industry challenges by:
Instrumentation Monthly May 2023
Building a data foundation: The Snowflake Manufacturing Data Cloud offers a single, fully-managed, secure platform for multi-cloud data consolidation with unified governance and elastic performance that supports virtually any scale of storage, compute, and users. It allows manufacturers to break down data silos by ingesting both IT and OT data and analysing it alongside third- party partner data.
MANUFACTURING DATA CLOUD POWERS SMART MANUFACTURING
Improving supply chain performance: Enable seamless data sharing and collaboration with partners for downstream and upstream visibility across an organisation’s entire supply chain coupling its own data with data from third-party partners and data from Snowflake Marketplace. By leveraging this data with SQL and Snowpark, Snowflake’s developer framework for Python, Java, and Scala, different teams can collaborate on the same data and build AI and ML models with confidence to forecast demand and enable critical use cases like supply chain control tower and spend analytics.
Powering smart manufacturing: Native support for semi-structured, structured, and unstructured high- volume Internet of Things (IoT) data in Snowflake enables manufacturers to keep operations running remotely by streamlining operations within and across manufacturing plants, while also leveraging shop floor data in near real-time to predict maintenance needs, analyse cycle time, improve product yield and quality, and meet sustainability goals.
Leveraging industry-leading network of manufacturing partners: Take advantage of a rich partner ecosystem and industry- specific, prebuilt templates to drive innovation, reduce time to value, and build more valuable solutions.
“Data has never been more critical as manufacturers embrace smart manufacturing initiatives and steer their companies into an increasingly digital- industrial world,” says Tim Long, global head of manufacturing at Snowflake. “The Snowflake Manufacturing Data Cloud and our ecosystem of partners gives manufacturers and their suppliers access to the data, applications, and services needed to effectively manage end-to-end supply chains, create new shop floor efficiencies, and deliver better products and services to their customers.”
Snowflake
snowflake.com 69
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