The Warehouse

The manufacturing industry is undergoing a digital transformation, and one of the key technologies driving this transformation is cloud analytics. Cloud analytics refers to the use of cloud-based data analytics platforms and tools that allow one to analyze substantial amounts of data quickly and easily. This can help manufacturing organizations to gain insights from their data and make more informed decisions.

There are several reasons why manufacturing organizations should consider adopting cloud analytics. First, cloud analytics can help manufacturing organizations to improve their operational efficiency. By analyzing data from across their operations, manufacturing organizations can ident...

Covid-19 had significant impact in the advancement of digital transformation. We witnessed the need for companies to be more agile and transform their traditional operating model. Post-pandemic these companies still feel a new set of pressure on the business to continue to innovate, develop a new customer experience, and improve operational efficiency while maintaining an acceptable level of output. Now more than ever, CIOs and Leadership need to collaborate and look to the unique advantages of cloud, data, and analytics as they build their digital efficiencies and IT roadmaps.

How did the Pandemic impact the manufacturing industry?

The COVID-19 pandemic has had a major impact on the manufac...

By: Jorel Digman

November 9, 2022

Data and Analytics projects can be complex and time-consuming, especially for an internal team with additional responsibilities. It requires the right technical skillset to realize your data’s full potential and see the benefits of a modern data stack built in the Snowflake Data Cloud.

Working with a Snowflake partner may be ideal when there is a lack of internal Snowflake Data Cloud expertise. A certified Snowflake partner can help you with data initiatives of all sizes and complexities whether you’re looking to deploy a data lake or data warehouse, improve existing data architecture and pipelines, or implement custom ML workflows with Snowpark.

1. Sno...

Today’s businesses continue to strive for data maturity and to create a culture that is data-driven and data-literate. But the perception remains that starting such a journey is expensive and time-consuming. There is a belief that a combination of high upstart costs and lengthy implementation time prevents the business from seeing any near-future value in its data and analytics investment. The reality, however, is that today’s cloud-based data platform technologies, specifically the triumvirate of Snowflake (data storage and compute), Matillion (data loading and transformation), and ThoughtSpot (data analytics and insight), enable rapid analytic ability with minimum initial inv...

The time it takes from beginning a data cloud initiative to realizing any of tangible value can be years.

After all, there is a lot to consider. First you need to ensure that there is business alignment, between the business and I.T., on what the short, mid, and long-term objectives are. Second, there is the small task of assessing your entire data estate. It is important to figure out with each vendor which modern data stack configuration, workload option, availability zone, and pricing plan is the optimal configuration for you.

Third, you need to build a migration plan, defining a strategy for each possible candidate analytical application and data set, that will drive value to the business ...

One of the challenges that many Snowflake administrators face is the daily monitoring of user and resource activity in their environment. The advantages of Snowflake's consumption-based pricing model (instantly-scalable compute sizing, usage-focused scheduling, etc.) are best employed when compute and storage activity is transparent to the business. Snowflake includes an ACCOUNT_USAGE view-based schema in the out-of-the-box Snowflake database than contains all the information related to account activity. This data can, of course, be directly queried like any other data, but wouldn't it be nice to have a single view of key metrics around data storage and activity that can be monitored day to ...

Pandata Group has always embraced and promoted the effectiveness of a robust data model as a means of “mapping” the enterprise data landscape (see our blog post here). Today this is more important than ever in the increasingly expanding cloud-native data analytics universe. A good data model provides not only a guideline for data engineers, but also a means of codifying and standardizing data usage from a governance perspective. Seamless integration of a data modeling tool into a cloud-native data management platform increases efficiency, collaboration and transparency. This is why we are so excited to be named a Gold Partner with SqlDBM, the leading cloud-based modeling solution...

If you are like many ETL developers you’ve struggled with an easy way to source cloud services data via REST API. Although standards are in place for REST API web services protocols, it seems that every vendor has their own variation of them, creating new challenges for each new source. Matillion’s cloud ELT product has long featured an API profile creator that sources from JSON files and creates RSD (Real Simple Discovery, an XML format) scripts for use with API query components. The effectiveness of this approach, however, is only as good as the quality of JSON files provided by the vendor.

Now, with version 1.47, Matillion introduces much more simplified functionality for extra...

Enterprises running SAP Business Warehouse (SAP BW, BW/4HANA and BW on HANA) are keeping a close eye on challengers like Snowflake. Is cloud data warehousing the answer to all the challenges for organisations with a large SAP footprint? And how does a cloud data warehouse fit into the data architecture? Should it replace SAP BW or is there still value in SAP BW?

Why do most enterprises with a large SAP footprint run SAP BW?

The dominant position of SAP BW is easy to explain from a historic perspective, but it would not do justice to SAP BW to ignore its current strengths as well. Let us start with the latter. SAP BW is still the only data warehouse platform which delivers all data warehouse f...

In 2015, I was fortunate enough to lead the sales development effort of a cloud-based supply chain visibility product. The product was geared toward the manufacturing sector to allow a more transparent and collaborative platform to enable information sharing. We leveraged the Salesforce cloud to build the application, and it was intended to support digital transformation efforts within the supply chain to optimize the flow of information, provide real-time data to the supplier, empower collaboration, and scale for adoption. Unfortunately, the ability to execute on the vision failed and it was tied to one key component – the part on delivering real-time data.

Let’s fast forward to...