A Cloud-Native Approach Democratizes Self-Service BI

A Cloud-Native Approach Democratizes Self-Service BI

A Cloud-Native Approach Democratizes Self-Service BI

The cloud is drastically changing the landscape of business intelligence (BI). New cloud applications have major advantages over traditional BI leaders, offering similar capabilities at a fraction of the cost. Cloud solutions enable major improvements in collaboration, security, integration, cost, customization, and support, but most importantly, they help remove the responsibility of BI from the IT department task list.

Better Collaboration Most BI tools put emphasis on producing flashy charts and reports, yet they abandon users at the most critical juncture: they have no mechanisms in place to allow users to take action on the analyzed results. A cloud-native approach easily enables integrated collaboration features that take over where the analysis ends with traditional BI tools. It provides users a centralized place in the cloud to facilitate a complete, end-to-end data analysis and decision-making lifecycle. Tasks can be created no matter where the user is browsing in the system with notifications automatically pushed to relevant parties through emails or text messages to remind them in real-time that there are actions that need to be taken. Users should not have to sift through emails or messages to check on the status of a task. All comments, feedback, uploaded related documents, and correspondences, as well as detailed history for tracking and auditing, can be made available in one accessible place.

Read Also:
Big Data: Big Opportunities

Higher Security With traditional extract, transform, load (ETL), the common practice is to tap into databases in the customers’ environment. Aside from requiring an exorbitant amount of time and resources from the IT staff, some BI tools even require opening inbound ports in the customers’ intranet to allow data to be pulled from their systems into the external BI application, which presents a significant security risk. A cloud-native architecture — when done right — would allow customers to push a selective portion of their data to the cloud, which only  requires authorizing outbound traffic and overall is a much safer approach as the customers’ intranet is not exposed to the outside world.

Improved Integration Ground-based or browser-based BI tools cannot easily compete with a cloud-native infrastructure when it comes to its inherent ability to seamlessly integrate outside data sources including spreadsheets, relational databases, web services, and networking devices. They also have the apparent advantage of integrating with third-party, cloud-based services and social media. For example, DrivenBI’s full-fledged, cloud-based platform SRK is integrated into Salesforce and shows up as a tab within Salesforce’s web page. Salesforce users can simply click on the SRK Analytics tab and see an integrated view and analysis of virtually any outside data from directly within the Salesforce platform. Only a cloud-native platform can accomplish this.

Read Also:
4 Data Virtualization Vendors to watch in 2017

Lowered Cost If an organization were to roll out an on-premise BI platform solution on a large scale, the licensing models would require a substantial capital investment plus the ongoing maintenance cost as applications and servers are installed. Capital investment also imposes vendor lock down; because a significant chunk of budget has already been spent, organizations may have no choice but to keep using what they’ve purchased even if later on their objectives have shifted or better solutions have emerged. Cloud-native solutions offer a simple yet flexible subscription-based pricing model. There is no capital investment, it’s easy to get started, and easy to scale up as the organization’s analysis demand increases.

Cloud-native infrastructures have a host of additional benefits as well. These include easy and constant access to support, simple customization, onboarding and sampling capabilities that don’t require sales teams, continuous free product upgrades, zero maintenance, and data cleaning and importing done by the people who own the data and need the analysis.

Read Also:
Why being a data scientist 'feels like being a magician'

 



Predictive Analytics Innovation summit San Diego
22 Feb

$200 off with code DATA200

Read Also:
Why being a data scientist 'feels like being a magician'
Read Also:
Big Data: Big Opportunities
Big Data Paris 2017
6 Mar
Big Data Paris 2017

15% off with code BDP17-7WDATA

Read Also:
The Data Science Puzzle, Revisited
Read Also:
Is Collaboration killing Creativity?

Leave a Reply

Your email address will not be published. Required fields are marked *