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5 Frequent Analytics Challenges for Snowflake Customers

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

GoodData and Snowflake make a wonderful mixture for operating your analytics app. Your subsequent query is why, proper? The reply is a bit long-winded however learn on to be taught in regards to the 5 distinctive use circumstances GoodData supplies to assist Snowflake knowledge customers.

1. Eradicate Change-request Overload

The State of affairs

In analytics, one measurement doesn’t match all. Finish customers will all the time be searching for one thing immediately suited to their wants (i.e., a distinct view of the information). This results in your crew will shortly turn out to be inundated with customization requests.

GoodData Resolution

That is the place multi-tenant structure, a well 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 may simply allow end-user customizations of dashboards and stories whereas making certain that every group’s knowledge is separate and safe. On prime of this, with plans priced per workspace quite than per person and the flexibleness so as to add limitless customers per workspace, you may shortly and simply scale your product alongside along with your Snowflake knowledge warehouse.

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

The State of affairs

Whether or not you propose to roll out analytics internally to staff or externally to clients, one of many predominant targets to your analytics resolution will seemingly be to supply analytics to as a lot of your finish customers as doable. Nonetheless, 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 software beneficial properties traction, you’ll quickly see knowledge volumes and concurrent person numbers develop, together with the prevalence of peak utilization occasions.

GoodData Resolution

On this occasion, elastically scalable analytics is required to enhance your Snowflake knowledge warehouse. GoodData’s elastic scalability effectively scales by knowledge quantity, person quantity, and value; 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 State of affairs

Whereas multi-tenant structure is one main requirement for offering self-service analytics, one other problem is knowing who your finish customers will probably be. They seemingly received’t all be analysts by career, which is why each step in the direction of ease of customization is effective. It additional helps to forestall customization requests that may in any other case go to your product, assist, or skilled companies groups.

GoodData Resolution

GoodData’s resolution is to implement reusable metrics. Reusable metrics is the simplest approach 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 Knowledge Silos and the Must Transfer Knowledge

The State of affairs

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 typical drawback for corporations rolling out analytics.

GoodData Resolution

Your Snowflake knowledge warehouse solves a part of the equation by offering one location for storing your whole knowledge from scattered knowledge sources. The opposite half of the equation? GoodData Cloud to immediately 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 State of affairs

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

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

Many corporations strategy this want through the use of a number of instruments and platforms that sit on prime of a shared database. Nonetheless, making certain analytics consistency throughout these varied instruments is troublesome as a result of every device can use a distinct knowledge mannequin and question language in addition to snapshots of knowledge from totally different occasions. 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 totally different values of the identical KPI.

GoodData Resolution

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

Headless BI schema
Guarantee constant analytics outcomes with headless BI.

Attempt GoodData + Snowflake

Need to be taught extra about how you can get essentially the most out of your Snowflake knowledge with GoodData? Learn extra about the advantages of our technical partnership or request a demo in the present day and we’ll provide you with an in-depth guided tour.

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