I recently engaged in a dialogue with one of our long-term clients from the manufacturing industry, wherein their Chief Information Officer posed an intriguing query:
“Dave, why is it not common to label all data as ‘Smart Data’?”
This query inspired and led me to pen this article delineating what it takes to categorize data as Smart Data.
What is Smart Data?
Simply put, it is data that has been processed and examined in a way that makes it helpful for decision-making and other uses is called Smart Data. Smart Data is organized, formatted, and frequently presented in a simple way to read and act upon, as opposed to raw data, which can be challenging to understand and use.
Generally, big data analytics, which is all about discovering patterns in massive amounts of data, and the idea of “Smart Data” are closely related. You can read further on Smart Data definition of terms from here.
How to use Smart Data in Manufacturing Industry
Smart Data can be extremely valuable in manufacturing because it can help in the optimization of production processes, the improvement of product quality, and the reduction of costs. Here are a few examples of Smart Data applications in manufacturing:
Predictive Maintenance
Implementing predictive maintenance is one way to use Smart Data in manufacturing. Manufacturers can identify when a piece of equipment will likely fail by accumulating data from IOT (Internet of Things) and other sources and analyzing trends and patterns. This empowers maintenance to be scheduled before a failure occurs, potentially saving money on downtime.
Quality Control
Smart Data can also be used to improve the manufacturing process for quality control. Manufacturers can identify defects or other issues in real-time by collecting data from sensors and cameras throughout the manufacturing process, allowing immediate corrective action.
Supply Chain Optimization
Smart Data can also be used to optimize manufacturing supply chain processes. Manufacturers can identify opportunities to improve efficiency, reduce costs, and improve delivery times by analyzing supplier data, inventory levels, and customer demand.
Production Optimization
Smart Data can be used to optimize manufacturing processes. Manufacturers can identify opportunities to improve efficiency and reduce waste by analyzing data on production rates, equipment usage, and other variables.
Overall, identifying the key performance indicators (KPIs) that are most important to the business and then collecting and analyzing data in a way that helps optimize those KPIs is the key to using Smart Data in manufacturing. Implementing new technologies, hiring data analysts, or collaborating with solutions providers like our team at Think AI, who specializes in smart data and analytics may be part of this.
5 Steps to Implement Smart Data in Manufacturing
Step 1: Identify the source of your data. Determine what kind of data you need to collect from each line of business, such as ERP, CRM, SCM, etc.
Step 2: Establish a secure connection between each source and your cloud environment. Use industry-leading encryption protocols and compliance certifications to ensure that all your sensitive data is kept safe from malicious third parties.
Step 3: Aggregate the collected data into one centralized repository using Data Integration tools such as Azure Data Factory or Synapse pipeline. This allows you to transform large amounts of data into valuable insights quickly.
Step 4: Analyze and visualize your collected data in real time using advanced analytics tools such as Power BI or ML (Machine Learning) Studio (Azure Machine Learning). These powerful tools enable you to develop predictive models with minimal coding required and gain insights into your operations faster than ever before.
Step 5: Leverage the power of machine learning and automation to automate tedious tasks and gain greater operational efficiency. You can also use automation to improve customer experiences, optimize existing processes, and lower costs associated with manual labor in manufacturing processes.
By following these steps, businesses can successfully leverage Smart Data in Manufacturing and maximize their success in the industry today!
How Azure Can Help
Azure is a cloud computing service offered by Microsoft that enables businesses to build, deploy, and manage applications and services through Microsoft-managed data centers. One of the key benefits of Azure is its ability to handle large amounts of data through its Big Data services, including tools for data storage, processing, and analysis.But beyond just handling Big Data, Azure offers a suite of services and tools that can help businesses move from Big Data to Smart Data. Here are a few examples:
Azure Machine Learning
This service allows businesses to build, train, and deploy machine learning models. By using this service, companies can analyze their data and gain insights that were previously difficult to obtain. For example, manufacturers can use machine learning models to predict equipment failures before they happen, allowing for proactive maintenance and reducing downtime.Azure Data Lake Storage
This service allows businesses to store and analyze massive amounts of structured and unstructured data. With this service, companies can gain insights into their data by running queries, performing analysis, and creating reports. For example, retailers can analyze customer buying patterns and preferences to make personalized recommendations and promotions.Azure Stream Analytics
This service allows businesses to analyze real-time data streams. By using this service, companies can react quickly to changing data and gain insights in real time. For example, transportation companies can use real-time analytics to optimize their delivery routes based on traffic conditions and customer demand.Azure Cognitive Services
This service allows businesses to add intelligent features to their applications without building them from scratch. This service allows businesses to add natural language processing, computer vision, and speech recognition to their applications. For example, customer service centers can use natural language processing to analyze customer inquiries and route them to the appropriate department.Microsoft Azure as is our experience in this field, is the best there is at offering a suite of services and tools that can help manufacturing companies make that transition. Whether machine learning, data storage, real-time analytics, or intelligent features, Azure has the tools all enterprise businesses need to gain insights from their data and make smart business decisions.