The Warehouse

BLOG & REsources

Dec
03
Creating Usage Dashboards with Snowsight

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 ...


Nov
08
Pandata Group and SqlDBM: Completing the Cloud Data Landscape

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...


Sep
30
Easily Connect to Any API Source From Matillion ELT

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...


Feb
25
Snowflake Data Cloud and the future of SAP BW

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...


Jan
28
Hey You! Get Onto My Cloud! Rise of the Data Cloud Pt 1

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...


Dec
18
Data Sharing and the “Internet of Databases”

The rise of personal computing in the 1980s and 90s led to a boom in business productivity that was transformative in its scope. Suddenly businesses had the power of what were formerly room-size computers on their desktops. This period saw the rise of the “knowledge worker” and the digitization of business.


But it was the impact of the internet that really drove business to the next level. All of those isolated desktop computers were now connected via a world wide web to enable communication, marketing and commerce without barriers. An open exchange of innovation and ideas fostered rapid growth, collaboration, and the global marketplace. The inter...


Jun
22
Matillion Data Loader: The Fast, Easy (and Free!) Way to Populate Your Cloud Data Warehouse

There is no question that companies are moving their on-premises data warehouses to the cloud at an increasing pace. The benefits of a cloud data warehouse (instant scalability, minimal up-front costs, rapid deployment, ubiquitous access, etc.) are being fully realized and appreciated by a growing number of enterprises both large and small. The major players in cloud DW (Snowflake, AWS Redshift, Azure Synapse, Google BigQuery) are all vying for market share, and the customers are seeing benefits from the varying and competitive costs and features of each platform.


But how do you get your data to the cloud? Isn’t the time and cost comparable to any data load project, whether it is on-pre...


Mar
30
Lakes, Swamps, and Puddles: The "Data Wetlands" Ecosystem

If you feel like you’re “drowning” in jargon and buzzwords surrounding the recent developments in data lakes and their ilk, you are not alone. A recent TDWI survey showed rapidly increasing adoption of data lakes as a source of big data analytics, though it also revealed barriers to success and confusion around implementation value. Much of this confusion stems from myths and misperceptions around the technical and business uses of a data lake. This article will examine the proper use of a data lake, and how proper governance can prevent it from becoming the dreaded data swamp.


To be clear, a data lake is not a data management platform, in that it is not an integrated, ce...


Mar
23
Where's the "T?" A look at ETL vs. ELT

In a previous blog post, we examined the differences between traditional ETL (extract, transform and load) and ELT, where the “heavy-lifting” of data transformation is handled by the robust and scalable (usually cloud-hosted) target platform. In today’s modern cloud data warehouse environment, ELT maximizes the speed at which data is staged and ingested, while leveraging massive computing power in the cloud to cleanse, aggregate and otherwise prepare that data for general consumption. But where is the best place to manage that transformation piece? Is it using cloud-friendly ETL tools, or is it within the management consoles of the cloud DWs themselves?


A common perception a...


May
29
Talend v. Matillion for Cloud Migration

The two leading ETL/ELT tools for cloud data migration are Talend and Matillion, and both are well-positioned for moving and transforming data into the modern data warehouse. So if you’re moving to any type of cloud-hosted DW, whether it is a cloud-dedicated warehouse such as Snowflake, or part of a larger cloud platform such as AWS Redshift, Azure SQL Data Warehouse or Google BigQuery, which tool should you use to move your existing on-prem data?


Both Talend and Matillion can source any kind of on-prem data and land it in a cloud-hosted data environment. They can also move data to and from AWS’s cloud data-storage S3 as well as Azure’s Blob storage (which can be used to s...


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