Cloud analytics programs deploy machine learning and AI for combining as well as modelling the different data sources. This is further critical for actionable insights and the detection of patterns. The superior dashboard feature lets businesses view KPI and ROI.
Last Updated on : 17 Sep, 2021
Found our list of Cloud Analytics Solutions helpful? We’re here to help you make the right choice and automate your business processes. Let’s discover some of the essential factors that you must consider to make a smarter decision!
As companies collect big data from multiple digital applications, their analysis and visualization become easy with the best cloud-based analytics tools. These applications have contributed to making business intelligence an accessible solution for enterprises of all types. After all, it is not just data visualization that you can perform using cloud analytics tools but also data synchronisation, data augmentation as well as interactive analytics.
All such data is easily shareable and you can filter it always for custom viewing.
Cloud analytics helps businesses scale their processes thereby reducing the costs of operating on-premise hardware solutions. This is one of the major reasons why cloud-based analytics are so important for organizations. Cloud analytics software as a service model is of the following types.
Keep your business running fast and smooth with analytics cloud core support features. The best part about using these solutions is they adapt easily to a fast-growing business while at the same time providing reliable infrastructure for data security. Let us go through similar such features of cloud analytics solutions to understand their functionality better.
With capabilities like natural language generation and processing, cloud analytics give immediate answers to queries in the form of data explanations/visualizations. Built-in AI-analytics makes these applications easily accessible for all as with little training, even those with not much experience can use cloud-based analytics software with ease.
Automated algorithms for machine learning help generate outliers and patterns in a data thus providing automated services for machine learning. Inbuilt predictive analytics are further helpful for forecasting and predicting upcoming outcomes at the snap of a finger.
You can conveniently use cloud analytics for drilling and filtering data for accurate data visualizations. The size of the data doesn't matter as the application is capable of processing large data sets. This equally works for efficient data modeling and cleansing too besides generating deep business insights.
The ability of data analytics to produce key business insights are mostly used for collaborative purposes. This feature along with the platform's machine learning functionality helps companies do predictive forecasting, strategic alignment and undertake informed decision making.
It is because of the solution's advanced analytics that combining transactions is easy for effective financial planning. Just from a single cloud interface, it is possible to undertake data-based budgeting, analysis and planning.
Cloud analytics offer business intelligence and analytical planning for more customized interactions. You can also customize templates, content, etc. with the available data models using the rapid prototyping feature.
In cloud analytics business software are available tailored widgets with data science abilities and composites. These widgets can be always adjusted hassle free with support from the application’s reusable and continuous user interface.
Hierarchies in data help with easy data management. The custom grouping module functions well for developing custom hierarchies for effective data management. You can later on use this information for other models, charts and stories. Custom ordering is critical for understanding data the right way.
Use cloud analytics for leveraging APIs for authenticating and adding analytics to the daily work. Once embedded, you can either publish it through a webpage or create interactions using chatbots. You can even use this feature for embedding analytics into another application.
Powerful natural language processing (NLP) is what you can definitely expect from the available best cloud analytics tools. NLP helps with powering text and speeches for conversational analysis and search. You can also expect some graph recommendations for enriching your data.
Based on the type of cloud analytics, the software is deployed in multiple ways as a service model. These are important for not just saving company costs but also improving a business’s performance. Some of the prominent industries that deploy these solutions are:
In short, cloud analytics tools are used by such industry verticals planning to undertake any of the following activities.
Cloud analytics are best used to enhance the capability and accessibility of doing complex analysis for large sets of data. These are important to businesses of all types for many reasons. Let us go through some of those.
Cloud analytics operates using a software-based system hosted on an internet platform. The entire system therefore works on a server within the data center. The larger a company is, the more powerful its server is for supporting cloud-based data analytics platform. Such data can be stored or retrieved as and when required. Enlisted here are the sources through which cloud-based analytics tools work.
Cloud analytics tools offer multiple features like data storage, analysis and ingestion. Along with such features, they also offer numerous benefits in the form of data visualization and business intelligence. Some other key benefits offered by the platform are:
A fast-growing business needs to be scalable enough to stay ahead of the competition. Cloud analytics tools are important here because they offer businesses the intelligence required for getting access to data in real-time. All these processes are highly flexible and cost saving.
Dara warehouse of cloud-based analytics solutions help with the consolidation of data. Such data can be consolidated from any type of source and processing this is also easy. Consolidated data is important for not just data mining but also developing prediction models in real-time.
The data processed by cloud analytics solutions help greatly the companies planning to scale their operations. Also, end users can use these as and when required so there is no hassle of compulsorily procuring it just for the sake of it. Such a data is collaborative in nature too as it can be shared with people across borders.
Cloud based analytics platform offer secured data access points for improving the data governance mechanism. Access is also available for undertaking granular controls for both auditing as well as identifying sources that have access to the data.
Servers operating on-premise quite often suffer from delivery and speed related issues. But this isn't so with analytics-based software. All of the platform's high-powered functions help with timely delivery of reports and queries.
Cloud services in data analytics are best for not just handling well response related issues but also reducing data latency. These are further helpful for managing emergency and BI queries in real-time. Companies also use this feature for scaling up their operations as well as efficiently managing the data warehouse.
Cloud analytics help organize the data in such a way that there is little to no possibility of data mismatch or delay. Such data is always updated so that there are predictable outcomes as well as quick decision making.
The interface of cloud analytics is consumer friendly as a result of which they have fast and flexible adaption capabilities. It is for this reason that organizations are able to scale their operations using these applications and adjust their data storage capacity as per the business's requirements.
Microsoft PowerPoint BI
Key features of Qlik:
Oracle Analytics Cloud
Key features of Oracle Analytics Cloud:
IBM Cognos Analytics
Key features of IBM Cognos Analytics:
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Q1 - How does cloud analytics work?
Cloud analytics combine predictive, BI and augmented analytics into a single cloud environment. This is important for both deriving business insights as well as analyzing the data. Other uses include:
Q2 - What are the steps to using cloud analytics?
Go through the steps enlisted here for understanding well how to start using Cloud Analytics programs:
Step 1: Login and go to the home screen for accessing data related information.
Step 2: Go to the stories section as you will get access here to data visualizations, graphs and charts.
Step 3: Click on either of the two option- Modeller or Story Mode- for creating models of all raw data.
Step 4: Import the data now for further exploring.
Q3 - How do cloud analytics solutions help with providing business intelligence?
Cloud based analytics software deploys the following features for performing business intelligence:
Q4 - Which are the best cloud analytics business software available in current times?
Some of the cloud analytics solutions available currently as software as a service model are:
Best for: Machine learning with SQL support
Best for: Multiple languages for programming
Best for: Data augmentation
Best for: Detailed reporting
Best for: HIPAA compliance