Thursday, September 29, 2022
HomeBusiness Intelligence5 Distinctive GoodData Use Circumstances for Snowflake Information Customers

5 Distinctive GoodData Use Circumstances for Snowflake Information Customers

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

GoodData and Snowflake make a superb 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 concerning the 5 distinctive use circumstances GoodData offers 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 at all times be searching for one thing instantly suited to their wants (i.e., a special view of the information). This results in your group will shortly grow to be inundated with customization requests.

GoodData Answer

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 consumer firm or person group, you’ll be able to simply allow end-user customizations of dashboards and reviews whereas guaranteeing that every group’s knowledge is separate and safe. On high of this, with plans priced per workspace quite than per person and the flexibleness so as to add limitless customers per workspace, you’ll be able to 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 State of affairs

Whether or not you propose to roll out analytics internally to workers or externally to prospects, one of many principal objectives in your analytics resolution will probably be to offer 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 positive factors traction, you’ll quickly see knowledge volumes and concurrent person numbers develop, together with the prevalence of peak utilization occasions.

GoodData Answer

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

GoodData Answer

GoodData’s resolution is to implement reusable metrics. Reusable metrics is the best method 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. Eradicate Information Silos and the Have to Transfer Information

The State of affairs

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

GoodData Answer

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 instantly question your Snowflake knowledge in actual time for at all times 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 instantly querying your Snowflake knowledge in actual time, finish customers at all times have entry to the freshest knowledge. On the identical time, you keep away from the necessity to transfer knowledge. Nonetheless, a profitable analytics software will probably contain a variety of customers, analysts, builders, and knowledge scientists who received’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, equivalent to utilizing their Python code with GoodData Python SDK.

Many firms method this want by utilizing a number of instruments and platforms that sit on high of a shared database. Nonetheless, guaranteeing analytics consistency throughout these numerous instruments is tough as a result of every instrument can use a special knowledge mannequin and question language in addition to snapshots of information from completely 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 completely different values of the identical KPI.

GoodData Answer

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 by way of normal 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

Wish to be taught extra about the right way to get probably the most out of your Snowflake knowledge with GoodData? Learn extra about the advantages of our technical partnership or request a demo immediately and we’ll provide you with an in-depth guided tour.



Please enter your comment!
Please enter your name here

Most Popular

Recent Comments