5 Distinctive GoodData Use Circumstances for Snowflake Information Customers

There are a plethora of instruments and platforms to select from relating to constructing  dashboards with Snowflake knowledge. For constructing interactive analytics apps with Snowflake, there’s GoodData.

GoodData and Snowflake make a superb mixture for working your analytics app. Your subsequent query is why, proper? The reply is a bit long-winded however learn on to study concerning the 5 distinctive use instances GoodData offers to help Snowflake knowledge customers.

1. Eradicate Change-request Overload

The Scenario

In analytics, one dimension doesn’t match all. Finish customers will all the time be on the lookout for one thing straight suited to their wants (i.e., a unique view of the info). This results in your staff will shortly develop into inundated with customization requests.

GoodData Resolution

That is the place multi-tenant structure, a widely known GoodData staple, turns into a necessity. By offering separate workspaces — devoted areas the place customers can analyze their knowledge and examine their dashboards — for every shopper firm or person group, you possibly can simply allow end-user customizations of dashboards and experiences whereas guaranteeing that every group’s knowledge is separate and safe. On prime of this, with plans priced per workspace reasonably than per person and the pliability so as to add limitless customers per workspace, you possibly can shortly and simply scale your product alongside along with your Snowflake knowledge warehouse.

2. Scale Analytics Alongside Snowflake Information Storage With out Sacrificing Efficiency

The Scenario

Whether or not you intend to roll out analytics internally to workers or externally to prospects, one of many essential objectives on your analytics answer will seemingly be to offer analytics to as a lot of your finish customers as potential. Nevertheless, the flipside to that is that as your end-user uptake will increase, so do the efficiency necessities of your knowledge storage and your analytics. As well as, profitable analytics functions are fairly taxing from an operational perspective. As your utility positive aspects traction, you’ll quickly see knowledge volumes and concurrent person numbers develop, together with the prevalence of peak utilization instances.

GoodData Resolution

On this occasion, elastically scalable analytics is required to enrich your Snowflake knowledge warehouse. GoodData’s elastic scalability effectively scales by knowledge quantity, person quantity, and price; in order your Snowflake knowledge storage grows, your analytics and person numbers can scale together with it — with out sacrificing efficiency.

3. Leverage Reusable Metrics to Empower Finish Customers

The Scenario

Whereas multi-tenant structure is one major requirement for offering self-service analytics, one other problem is knowing who your finish customers shall be. They seemingly gained’t all be analysts by occupation, which is why each step in the direction of ease of customization is effective. It additional helps to stop customization requests that will in any other case go to your product, help, or skilled providers groups.

GoodData Resolution

GoodData’s answer is to implement reusable metrics. Reusable metrics is the simplest solution to obtain ease of customization. By making a semantic mannequin and defining base metrics that your finish customers can later use when creating their particular metrics as easy arithmetic expressions, your finish customers can handle their analytics effectively and confidently.

Data model example
Outline base metrics your finish customers can reuse.
Logical data model with stacks of technical and business metrics
Obtain ease of customization with reusable metrics.

4. Remove Information Silos and the Have to Transfer Information

The Scenario

With knowledge being collected from a number of sources and moved between departments and functions, the prevalence of knowledge silos and rancid knowledge is a standard drawback for firms rolling out analytics.

GoodData Resolution

Your Snowflake knowledge warehouse solves a part of the equation by offering one location for storing all your knowledge from scattered knowledge sources. The opposite half of the equation? GoodData Cloud to straight question your Snowflake knowledge in actual time for all the time up-to-date knowledge analytics — with out the necessity to transfer knowledge whereas additionally eliminating knowledge silos.

5. Keep away from Metrics Inconsistencies

The Scenario

As described above, with an analytics answer straight querying your Snowflake knowledge in actual time, finish customers all the time have entry to the freshest knowledge. On the identical time, you keep away from the necessity to transfer knowledge. Nevertheless, a profitable analytics utility will seemingly contain a range of customers, analysts, builders, and knowledge scientists who gained’t be glad with simply interactive knowledge visualizations and dashboards.

They’ll need to use the analytics ends in a number of different functions (e.g., BI instruments, ML/AI notebooks, and many others.) that type a part of their workflow and mix these leveraged metrics with their queries. As a substitute of counting on outdated knowledge exports, they’ll need to connect with the semantic layer and get real-time metrics, akin to utilizing their Python code with GoodData Python SDK.

Many firms strategy this want through the use of a number of instruments and platforms that sit on prime of a shared database. Nevertheless, guaranteeing analytics consistency throughout these numerous instruments is tough as a result of every instrument can use a unique knowledge mannequin and question language in addition to snapshots of knowledge from completely different instances. All of those variations could cause customers to make use of ungoverned calculations of their instruments. Unsurprisingly, this results in knowledge inconsistencies when 4 customers report 4 completely different values of the identical KPI.

GoodData Resolution

Right here is the place headless BI is the answer. Headless BI permits finish customers to attach on to the analytics engine embedded in your functions through commonplace APIs and protocols (e.g., JDBC or ODBC) to offer up-to-date, clearly outlined knowledge.

Headless BI schema
Guarantee constant analytics outcomes with headless BI.

Strive GoodData + Snowflake

Need to study extra about how one can get probably the most out of your Snowflake knowledge with GoodData? Learn extra about the advantages of our technical partnership or request a demo right this moment and we’ll offer you an in-depth guided tour.

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