cloud-based analytics tools

Cloud analytics has enabled the business to find actionable insights when it shakes its hand with Big data analytics. As there is a profusion of data from a wide array of digital applications, it’s no surprise that cloud analytics has revolutionized those big data along with business intelligence along with the help of cloud-based analytics tools. Though many SaaS tools come with built-in analytics, one of the main reasons for using this plethora of cloud-based analytics tools is to combine different data sets from various data sources to use it with business intelligence tools.

These cloud-based analytics tools represent clear data visualization through the plotting of analyzed data. Furthermore, as the whole process is cloud-based, we are getting synchronized and shared data.

There are numerous analytics programs in the market, and based on that, the cloud-based analytics tools. So, how do you measure which one is the best? We will discuss the trends, of course, but in one term, the best are the ones that can scale responsively and support the business models of the company. Additionally, cloud-based analytics tools have started to close the gap between modern enterprises’ offerings and legacy systems to grow and complete.

How do you select the most suitable cloud-based analytics tools?

Cloud-based analytics tools are complex systems. Hence, while selecting the cloud-based analytics tools, you need to consider a range of factors. Here are some of the checkpoints to select cloud analytics tool – 

Does the tool support the agile-based approach? The Agile development methodology dominates today’s enterprise. Additionally, analytics tools that implement agile methodology help to attain results fastest. Hence, consider whether your cloud platform vendor provides you the flexibility of taking the agile-based approach?

Does the cloud analytics vendor offer a short term contract? The majority of enterprises acquiring cloud analytics tools solutions are moving for short-term contracts between 12 to 24 months. These short-term contracts are justified considering the budgeting and spending constraints within business units. Also, while renewing the service, you can negotiate a better price and more significant influence on product and service roadmaps in the short-term. Also, it’s not only a budgetary factor; there are technical reasons too. As the new algorithms, platforms, and apps are extending today, shorter contracts free up enterprises to get out in front of the innovation curve and make it work to their advantage.

Do the analytics vendor update algorithms on-time? The algorithm economy is where the competitors are moving fast to obtain more significant insights using cloud platforms. Also, the algorithms are updated from time to time, which will eventually change the competitive landscape, especially for manufacturing and service industries.

How quickly are you doing analytics using the tool? As a user, you need to benchmark cloud analytics tools to quickly add advanced cognitive analytics and prescriptive apps to the workflow level. Here the main challenge is that most of the work is done reactively. In this context, machine learning and advanced algorithms play a significant role in the coming years.

Related post – What is Cloud analytics and related faqs

Top 5 Cloud-based analytics tools

Azure Stream analytics

Azure Stream Analytics is the serverless real-time analytics solution from Microsoft’s powerful Azure cloud computing platform, which aims to serve mission-critical workload. It builds an end-to-end serverless streaming pipeline with just a few clicks. Hence, you can transition from zero to production in minutes using SQL. Additionally, it is easily extensible with custom code and built-in machine learning capabilities for more advanced scenarios. Run your most demanding workloads with the confidence of a financially backed SLA.

The features, as described by Microsoft, are as below:

  • End-to-end analytics pipeline that is production-ready in minutes with familiar SQL syntax and extensible with JavaScript and C# custom code
  • Rapid scalability with the elastic capacity to build robust streaming data pipelines and analyze millions of events at sub-second latencies
  • Hybrid architectures for stream processing with the ability to run the same queries in the cloud and on the edge
  • Enterprise-grade reliability with built-in recovery and built-in machine learning capabilities for advanced scenarios
  • Run complex analytics with no need to learn new processing frameworks or provision virtual machines (VMs) or clusters. Use familiar SQL language that is extensible with JavaScript and C# custom code for more advanced use cases. Easily enable scenarios like low-latency dashboarding, streaming ETL, and real-time alerting with one-click integration across sources and sinks.
  • Get guaranteed “exactly once” event processing with 99.9% availability and built-in recovery capabilities. Easily set up continuous integration and continuous delivery (CI-CD) pipeline and achieve sub-second latencies on your most demanding workloads.
  • Bring real-time insights and analytics capabilities closer to where your data originates. Enable new scenarios with proper hybrid architectures for stream processing and run the same query in the cloud or on the edge.
  • Take advantage of built-in machine learning (ML) models to shorten the time to insights. Use ML-based capabilities to perform anomaly detection directly in your streaming jobs with Azure Stream Analytics. [Ref:5]

AWS analytics

AWS Analytics for Amazon Web Services offers a wide range of analytics services, which covers every feature of the powerful cloud platform based on your demand of information you are looking for.

AWS gives you the broadest and deepest portfolio of purpose-built analytics services optimized for your unique analytics use cases. These services are all designed to be the best in class, which means you never have to compromise on performance, scale, or cost when using them. For example, Amazon Redshift is 3x faster, and at least 50% less expensive than other cloud data warehouses. Spark on Amazon EMR runs 1.7x faster than standard Apache Spark 3.0, and you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions. [Ref: 1]

It offers you the option of unified governance, one of the most critical criteria of modern analytics. This means the customer’s ability to authorize, manage, and audit access to data. This is challenging indeed because of its complexity, time consumption, and chances of error. AWS gives you –

  • centralized access control and policies
  • column level filtering of data

No other vendor gives you this governance capability to manage access to all of your data across your data lake and your purpose-built data stores from a single place.

Primarily four uses cases are covered with AWS cloud analytics –

  • Data warehousing
  • Big data processing
  • Real-time analytics
  • Operational analytics

IBM Cognos Analytics

IBM Cognos Analytics is a business intelligence platform that is an AI-infused business intelligence solution that accelerates data preparation, analysis, and reporting for smarter business. As it uses machine learning and AI, it discovers patterns of information using advanced pattern detection leveraging actionable insights with answers. Natural language processing plays a significant part here.

You can drive certainty in your decision-making with AI-powered analytics. IBM offers an industry-leading BI solution that empowers users to execute smarter data discovery and tell the story of their data with stunning visualizations. The release of IBM Cognos® 11.1.7 delivers new innovations. Now users can access analytics anywhere at any time with a new mobile app and higher performance, providing reliable insights in real-time. [Ref 2]

You can run Cognos Analytics from the cloud or on your premises. Either way, data can be uploaded to the program in the form of spreadsheets or CSV files where the data sources can be combined and modeled. Cognos believes in the best chart types for visualization, and their reports have geospatial-mapping capabilities. Charts can also be augmented with other media, such as voiceovers and interactive elements.

There’s a free 30-day trial available, which allows full use of the product.

Domo

Domo is a business cloud company that claims that it can leverage BI at cloud scale at record time. Domo can dynamically integrate data from thousands of data sources and finally turn data into visualization. Furthermore, it extends BI directly into applications and workflows. Domo makes everyone a part of the BI team, which accelerates a data-driven culture in the company.

What does Domo do?

  • Keep your workforce connected with mobile data tools and custom alerts.
  • Make better decisions with predictive tools and AutoML to surface insights.
  • Embed analytics and dashboards into portals and software or connect them across Domo-hosted instances.
  • Empower self-service analytics with enterprise-grade security and complete governance. [Ref 3]

Domo modernizes your business with its intelligent apps.

  • Discover enterprise-ready intelligent apps through Domo’s Appstore.
  • Leverage Domo’s cloud platform, security, file management, and distribution to quickly build intelligent applications.
  • Create your own low-code intelligent apps or partner with Domo to swiftly build customer apps to meet your business needs. 
  • Write data back to systems and automate to create a system of intelligence and action. [Ref 3]

Domo offers a free 30-day trial allowing you to try the service for yourself.

Zoho Analytics

Zoho Analytics comes with an easy-to-use dashboard that is user friendly. It is part of Zoho’s software suite but also works as a stand-alone package. Transform vast amounts of raw data into actionable reports and dashboards. Track your key business metrics; see longtime trends, identify outliers, and unearth hidden insights.

What can you do with Zoho analytics?

Get and blend data from multiple sources: Get data from a wide range of sources. Blend them together to create cross-functional reports and dashboards to view your business health across departments.

Visually analyze your business data: Create reports and dashboards with our reporting tool’s easy to use drag-and-drop designer. Use different visualization options to drill down to specifics.

Collaborate securely online: Share/publish your reports with your colleagues. Add comments and hold conversations. Set smart data alerts to alert you when outliers or anomalies happen.

Embedded analytics: Get powerful embedded analytics and BI tool in your own brand name that can be embedded within your own product, application, or accessed from your portal or website.

[Ref 4:]

Final Thought

The bottom line is that the scalability, deployment speed, agility, and rapid prototyping capability of analytics workflows on cloud-based analytics platforms are high. As a result, they are winning out over more costly and time-consuming alternative tools that require IT’s time and attention.

Different cloud-based analytics tools offer different pros and cons with each solution, and not all of these systems are the best for your organization. Hence, match your requirements with cloud analytics tools, compare platform features and pricing, and then decide.

Do you agree with the above-mentioned cloud-based analytics ‘ picks? What cloud analytics platform do you use? And how is the feedback for the same? Let us know in the comments!

References:

Ref1: https://aws.amazon.com/big-data/datalakes-and-analytics/

Ref 2: https://www.ibm.com/products/cognos-analytics

Ref 3: https://www.domo.com/platform#visualize-and-analyze

Ref 4: https://www.zoho.com/analytics/

Ref 5: https://azure.microsoft.com/en-in/services/stream-analytics/#overview

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