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Building Data Pipelines with Kubernetes


Data pipelines are a set of processes that move data from one place to another, typically from the source of data to a storage system. These processes involve data extraction from various sources, transformation to fit business or technical needs, and loading into a final destination for analysis or reporting. The goal is to automate […]

The post Building Data Pipelines with Kubernetes appeared first on DATAVERSITY.


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Author: Gilad David Maayan

Data Analytics for Supply Chain Managers

If you haven’t already seen Astrid Eira’s article in FinancesOnline, “14 Supply Chain Trends for 2022/2023: New Predictions To Watch Out For”, I highly recommend it for insights into current supply chain developments and challenges. Eira identifies analytics as the top technology priority in the supply chain industry, with 62% of organizations reporting limited visibility. Here are some of Eira’s trends related to supply chain analytics use cases and how the Avalanche Cloud Data Platform provides the modern foundation needed to make it easier to support complex supply chain analytics requirements.

Supply Chain Sustainability

According to Eira, companies are expected to make their supply chains more eco-friendly. This means that companies will need to leverage supplier data and transportation data, and more in real-time to enhance their environmental, social and governance (ESG) efforts. With better visibility into buildings, transportation, and production equipment, not only can businesses build a more sustainable chain, but they can also realize significant cost savings through greater efficiency.

With built-in integration, management and analytics, the Avalanche Cloud Data Platform helps companies easily aggregate and analyze massive amounts of supply chain data to gain data-driven insights for optimizing their ESG initiatives.

The Supply Chain Control Tower

Eira believes that the supply chain control tower will become more important as companies adopt Supply Chain as a Service (SCaaS) and outsource more supply chain functions. As a result, smaller in-house teams will need the assistance of a supply chain control tower to provide an end-to-end view of the supply chain. A control tower captures real-time operational data from across the supply chain to improve decision making.

The Avalanche platform helps deliver this end-to-end visibility. It can serve as a single source of truth from sourcing to delivery for all supply chain partners. Users can see and adapt to changing demand and supply scenarios across the world and resolve critical issues in real time. In addition to fast information delivery using the cloud, the Avalanche Cloud Data Platform can embed analytics within day-to-day supply chain management tools and applications to deliver data in the right context, allowing the supply chain management team to make better decisions faster.

Edge to Cloud

Eira also points out the increasing use of Internet of Things (IoT) technology in the supply chain to track shipments and deliveries, provide visibility into production and maintenance, and spot equipment problems faster. These IoT trends indicate the need for edge to cloud where data is generated at the edge, stored, processed, and analyzed in the cloud.

The Avalanche Cloud Data Platform is uniquely capable of delivering comprehensive edge to cloud capabilities in a single solution. It includes Zen, an embedded database suited to applications that run on edge devices, with zero administration and small footprint requirements. The Avalanche Cloud Data Platform transforms, orchestrates, and stores Zen data for analysis.

Artificial Intelligence

Another trend Eira discusses is the growing use of artificial intelligence (AI) for supply chain automation. For example, companies use predictive analytics to forecast demand based on historical data. This helps them adjust production, inventory levels, and improve sales and operations planning processes.

The Avalanche Cloud Data Platform is ideally suited for AI with the following capabilities:

  1. Supports rapid machine learning model training and retraining on fresh data.
  2. Scales to several hundred terabytes of data to analyze large data sets instead of just using data samples or subsets of data.
  3. Allows a model and scoring data to be in the same database, reducing the time and effort that data movement would require.
  4. Gives data scientists a wide range of tools and libraries to solve their challenges.

This discussion of supply chain sustainability, the supply chain control tower, edge to cloud, and AI just scratch the surface of what’s possible with supply chain analytics. To learn more about how the Avalanche Cloud Data Platform, contact our data analytics experts. Here’s some additional material if you would like to learn more:

·      The Power of Real-time Supply Chain Analytics

·      Actian for Manufacturing

·      Embedded Database Use Cases

The post Data Analytics for Supply Chain Managers appeared first on Actian.


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Author: Teresa Wingfield