When Cloud Meets BI: Cloud BI Solutions to Refine Your Business

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Cloud-based intelligence is gaining traction as the costs of data analysis are growing. But is it worth your investment? Find out in our article!

The cloud has long been touted as the savior of all business operations. Its speed, scale, innovation, and productivity gains are fundamental to the pursuit of broader digital business opportunities. Business intelligence is another pillar of skyrocketing value creation that allows organizations to analyze, report, and act on data at scale.

But what if you cross-breed these two? 54% of enterprises already did it and reported cloud-based BI solutions being essential to their current and future initiatives. Let’s see why yet another business infrastructure blends well with cloud computing.

What is cloud business intelligence?

Cloud-based business intelligence, or cloud BI, refers to the process of consolidating and crunching data with the help of cloud computing – either partially or fully. With unmatched scalability and processing speed offered by the cloud, companies can pull new meanings from their data across a wide range of devices and applications with none of the overheads associated with locally run infrastructures.

How does cloud BI work?

When it comes to deploying business intelligence on the cloud, organizations have three options: private, public, or hybrid solutions. While each of the three, abstracts, pools, and shares scalable computing resources across a network, they all differ by the control level over the infrastructures.

Private

This type of cloud-based analytics business intelligence is premised on rented, vendor-owned data centers. Unlike the popular opinion, privately-run cloud, BI can be located off-premises, yet it’s still dedicated exclusively to the needs of a particular company. This type of cloud-based business intelligence software is usually a go-to option for compliance-heavy organizations that have to adhere to regulatory compliances.

Public

Public cloud business intelligence is accessed as an on-demand software-as-a-service solution. Public BI applications cater to multiple companies and are under a full dominion of a cloud provider. As the cost is divided among all tenants, public business intelligence is greatly favored among small- and mid-sized businesses with middle to low regulatory compliance needs.

Hybrid

This access model is the middle ground between private and public environments. A hybrid cloud infrastructure runs business-critical workloads on private clouds, while less sensitive data flows into the public cloud assets. The two environments operate seamlessly side-by-side and allow workloads to move between the two interconnected environments.

Cloud-based business intelligence architecture

Cloud BI solutions thrive on an integrated and unified data hub that further sets data analytics in motion. That’s why cloud business intelligence tools need a data warehouse to manage disparate data flows and bring data from various sources under one hood.

A data warehouse has the upper hand over on-premise warehouses as a more scalable, flexible, and all-in data storage option with less routine management burden and a shared pool of computing resources. Companies are no longer shackled to physical data centers and can dynamically ramp up or down their storages to meet evolving business needs.

But how does all data end up in a warehouse? A cloud BI ETL (extract, transform, load) process is what helps transform raw insights and inject storage-ready bits from multiple points into a single data warehouse. Using cloud-based ETL technology, companies can automate the whole data lifecycle and copy source data to the warehouse destination regularly to facilitate data import.

Besides a data warehouse and ETL, organizations need a few other add-ons to stoke up their cloud BI software. According to a report, users give high marks to relational database support as an element that connects data from different tables (transactions, customer information, etc.) to a cloud data warehouse for a more comprehensive assessment of business performance.

Compatibility with on-premise digital estates such as ERP and CRM and open client connectors are also critical priorities for seamless data sharing with cloud architecture. NoSQL source support sits on the sidelines of architectural priorities, suggesting that the public cloud is mostly viewed in the context of standalone applications.

What can you gain from cloud BI solutions?

By 2028, the global cloud analytics market is slated to reach over $86 billion, driven by the data connectivity imperative. Here are the core advantages of cloud BI that contribute to its proliferation.

Fast and easy implementation

Since cloud business intelligence doesn’t require any additional hardware or software installations and cluster set-ups, it takes off faster compared with on-premise ecosystems. A wide range of baked-in features, modules, and governance measures put up to the speed and ease of implementation provided that you know your way around all configurations.

Ease of use

Cloud BI tools enable self-service insight gathering through simple questions, easy visual analysis, and an intuitive web-based authoring interface. The miscellany of guided workflows suggests minimal adoption barriers for cloud analysis, resulting in higher user buy-in and a low learning curve.

Scalable resources

A cloud architecture auto-scales to growing users with high availability and dynamically allocates resources to match evolving BI initiatives. It means that teams don’t have to build up databases for high workloads immediately, and can easily scale up or down computing resources on an as-needed basis.

Cost savings

The cost reduction potential of cloud BI stems from lower CapEx as you don’t have to spend money on hardware. It gets tricker with operational expenditure where a medley of configurations enters the equation. Without a dedicated team, you risk throwing money down the configuration drain as you fine-tune your cloud domain.

Advanced data sharing

Cloud analytics is the epitome of collaborative knowledge-sharing and joint workflows as it allows any team member seamless and on-the-go access to the data estate. The infrastructure also allows you to blend data from on-premise and cloud, and augment it with real-time and web-based insights within a single interface.

Automatic updates

Update management is an irritating inconvenience for on-premise estates that gets hassle-free in a cloud infrastructure. Cloud service providers usually cover hosting, maintenance, and updates so that you can focus on mission-critical tasks.

Rapid data processing

For complex and hefty analysis, companies can leverage high-performance computing available on the cloud. Available at an additional cost, cloud rapid data processing can speed up resource-intensive analysis without a swath of hardware while rechecking your input for maximum accuracy and consistency.

Ease of integration

Although both local and cloud business intelligence boast rich data integration potential, cloud tools still excel at built-in data connectors. Companies can instantly go from data to insight to visual display by integrating all data into a cohesive whole from databases, online services, and other supported data connection types. Conversely, on-premise solutions require a more dedicated effort to set up an integrated blanket of data due to the lack of ready-to-go data connectors.

Security & Compliance

Cloud BI compliance benchmarks provide good baseline security as cloud providers focus on the ever-changing regulatory landscape. A BI solution helps you take care of common industry-specific standards and local regulations by offering robust built-in security measures and compliance enablers- gift-wrapped.

Analytics tools keep your guard up with data encryption, automated security updates, multi-tiered caching, and advanced authentication measures. It’s like having a whole team of data security experts at your disposal instead of wading through guidelines and acting on your own.

What to pay attention to in cloud-based business intelligence software?

A business intelligence tool is an umbrella interface made up of various components to uncover, analyze, and report data from a wide array of data sources. Although the stuffing differs by solution, any BI tool needs four main ingredients to convey the taste of data excellence.

Data management

From data quality to security to governance, an end-to-end data management strategy demands a multidisciplinary approach reinforced by the company, its people, and its digital ecosystem. A cloud-based BI tool cannot make up for a holistic data management regimen. But it can become your most integral asset that promotes better data health by integrating, contextualizing, analyzing, and protecting your data assets.

Some BI solutions provide in-built data management capabilities that help you prepare, model, and bring your data to life within a single interface. The Microsoft BI stack is a prominent example of end-to-end analytics architecture that guides each step of your business intelligence journey with a variety of purpose-built tools.

Advanced analytics

Complex analytics capabilities turn descriptive insights into prescriptive knowledge. This is why your business intelligence system should be premised on built-in AI capabilities, such as image tagging, sentiment analysis, and others, to make every bit of data work to your advantage.

Data visualization and reporting

Visualizations make insights more digestible for all decision-makers and help your data tell stories, instead of throwing puzzles in a spreadsheet of numbers. A BI tool should allow you to slice, filter, highlight, and drill into visualizations with built-in charts, graphs, and maps, along with custom drag-and-drop dashboards.

Collaboration

Finally, a tool should promote unified team efforts through multiple collaboration channels and sharing options. Some solutions also have a presentation mode to display reports, an embedded functionality for seamless data-sharing, and shared datasets for user-based report creation.

According to a report, other BI mainstays include an ad-hoc query for more niche business questions, production reporting for manufacturing companies, and self-service capabilities for IT-independent business units. The percentage distribution also suggests a direct correlation between the set of features and a user’s job function.

Who can benefit from cloud BI solutions the most?

Over the last few years, business intelligence has emerged as a game changer for different industries. However, some verticals have hit the mark with cloud analysis.

According to Statista, marketing and sales stand as the biggest gainers of cloud BI, with 50% of respondents marking this asset as critical for their importance. The R&D area has seen a growing importance of BI as well, – with 42.5% of respondents reporting its critical potential.

Another report demonstrates a weighted-mean interest in cloud analytics in higher education and customer services, while healthcare and financial services are still testing the waters of business intelligence.

This upward tendency in certain industries implies a tie-in to the growing data in the fields, the demand for greater business flexibility, and the need to measure business performance at scale. All these and more are conveniently packed into cloud business intelligence.

Which cloud BI provider to choose?

Your business intelligence initiative doesn’t need to be a big bang from the start. You can start small by testing popular SaaS solutions from renowned cloud providers. Microsoft Azure is an acknowledged leader in the field, with 77% of users reporting its critical or very important impact.

The positive user sentiment is well justified for Microsoft Azure as it offers the complete suite of data analytics, BI, and visualization tools on top of its mature, cloud ecosystem. Backed by a multi-layered security approach with 96 compliance offerings, Microsoft Azure helps companies use their data strategically and safely with no back-and-force of third-party tools.

The dominance of Microsoft Azure is indisputable. This ecosystem has your data worries covered on all tracks with data lakes, Power BI, Azure Synapse Analysis, and whatnot can be built with Azure Stack.

— Ivan Dubouski, BI Lead Specialist, *instinctools

As a certified Microsoft Azure partner, *instinctools helps companies accelerate Power BI adoption and optimize this cloud ecosystem to fit their unique business and data needs.

Amazon Web Services and Google Cloud Platform also sit on top of leading BI platforms with 66% and 41% combined critical and very important scores, respectively. Both allow users to explore data through interactive dashboards, pattern detection, and outliers powered by machine learning.

The powerful duo of business intelligence and cloud

In an increasingly winner-takes-all business environment, any organization that doesn’t put its data to good use lives on borrowed time. Cloud BI tools help you achieve business impact with data and get a comprehensive perspective — at any time, at reduced costs, and at your convenience. Powered with analytics and visuals, cloud BI solutions give voice to your data and help you translate the language of numbers into the language of action.


The article was originally published here.