The development of the Cloud in Business Intelligence

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Cloud computing defines access to IT services whenever you want, via the Internet and a provider. The services offered range from file storage to artificial intelligence, including network management, application, and software hosting. The cloud’s goal is to make it easy for the user to access these services so that they don’t have to worry about the actual location of the hardware they are using.
This model of cloud computing offers a considerable advantage to companies of all sectors present on the Internet.

It is then obvious that the Business intelligence community is not left behind on this notion.
Today, companies have access to an immense amount of data to accelerate their growth and make decisions. Cloud BI tools become essential. They allow the visualization of a company’s data to all employees to facilitate decision-making.
In recent years, we have seen companies specializing in BI software transform and become more accessible with cloud solutions.
With remote, it is now essential for companies to be equipped with cloud solutions and collaborative tools.

Take the example of Qlik, which started in 1993 with the launch of QlikView business intelligence software and a local or on-premise server installation. It is now possible to deploy its data from QlikView to cloud platforms such as Azure or AWS. In 2014 Qlik launched a new, more modern solution that meets its users’ new expectations, Qlik Sense, available in SaaS mode, allowing users to share their applications with others. In June 2019, Qlik perfected its offer and launched into the 3rd generation of Business Intelligence by proposing a Cloud-First strategy and a new version of Qlik Sense, Qlik Sense Business, and offering the Qlik Sense Enterprise service to small and medium-sized companies and opening the doors to 3rd generation analytics.
This approach is a part of a policy democratize data and a multi-cloud.

In 2020 and for the first time, most people, 54%, consider that business intelligence cloud is necessary, and 53% say they use it regularly. We notice an additional investment from the users to increase their utilization of the cloud in their analytical strategy.
Only a few companies, 15%, said they do not use any cloud BI solutions.
The private cloud is still the most used BI applications model, but it could be considered a first step towards the public cloud. Indeed, the current trend is towards a transition of companies on this second solution.

In this article we will see Qlik’s approach to the cloud, the advantages and disadvantages of the cloud, and how to choose the right solution for your company.

1- The Cloud, Qlik’s priority (SaaS-first)
2- The different options of cloud
3- Advantages and disadvantages of the cloud
4- What to consider before choosing a cloud analytics platform

 

1- The Cloud, Qlik’s priority (SaaS-first)

The most used form of cloud is Saas, Software as a Service. The software is installed on remote servers that can be used from any computer via the Internet.

This solution quickly appeared inevitable for Qlik and its services. It quickly became the leading company in the SaaS analytical platform sector.
The company follows the cloud-first trend and relies on its innovative technologies such as Associative Difference and its cloud architecture based on Kubernetes. Thank to it, Qlik Sense Enterprise can be entirely available on Qlik Cloud Services.
Qlik then meets its users’ needs who want more flexibility and choice when deploying their analytics platform.

The April and June 2019 releases of Qlik Sense support the company’s focus on making data accessible and easy to use.
Qlik wants to equitably equip companies with data management tools and make analysis as easy as possible, thanks to augmented intelligence and the cloud for a better distribution of information and data.
The SaaS offered by Qlik allows free access to any company member working with data, whether he is an analyst, CEO, or sales. This simplified access to data improves transparency, consistency, and information exchange within an organization, making it much easier to make decisions and strategic changes.
Qlik’s offering is based on a subscription-only, single license model that can be used both on-premise and in the cloud. The offering is customer-centric, not service-centric.
With its multi-cloud and Saas-first strategy, Qlik enables different analytics choices in the cloud, either through Qlik Cloud Services Saas or via Kubernetes in a private or public cloud. Qlik’s cloud offering also includes additional services and options such as full certification on Google Cloud Platform, Azure, and Amazon; the ability to install and manage its multi-cloud and multi-site deployments in one; Deployment options accompanied by a new management experience that simplifies the user experience, content and licensing across different environments.

In the June 2019 release, Qlik Sense introduced its innovations around augmented intelligence, Insight Advisor enhancements, direct import of learnings into Qlik Cloud Services. This product set provides transparency for members of the same organization, new direct cloud connections to applications like Salesforce and SAP, access to QlikView through Qlik Cloud, a mobile Qlik Sense version for Blackberry, as well as support with MobileIron EMM, which then enables mobile collaboration with push notifications on Android and IOS.
Besides, Qlik Sense Enterprise makes it easier for QlikView users to switch to Qlik Sense if they want to use both software. This service is accomplished through a new unified license that allows companies to unlock QlikView and Qlik Sense with a single license key and links to use the Qlik Sense environment options on Qlik View. This new feature allows end-user access to all Qlik applications and Qlik View user companies to take advantage of the latest Qlik innovations through Qlik Sense.

 

2- The different options of cloud

Let’s take a look at the different types of analytic clouds:

  • Public cloud: several companies share services, but applications and data are hidden. This solution allows you to limit costs while offering better performance and ease of management.
  • Private cloud: services are dedicated to a single company. Companies with more sensitive data such as medical companies, banks, or ministries are favored because this type of cloud offers stronger security.
  • Hybrid: This is a mix of private and public clouds. Hybrid solution allows you to keep your sensitive data in a more secure universe and your usual data in a less expensive public cloud.
  • Hybrid and multi-cloud: To better control the storage of their data and strengthen their security, companies adopt an approach combining public, private and on-premises clouds. This solution also allows companies to optimize the evolution and the total cost of their data.

 

Let’s take a look at Qlik’s cloud analytics offerings:

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With the deployment of Qlik Sense Enterprise on Windows, users can distribute their applications in a single-tenant (one tenant) or on-premise cloud to one or both of Qlik’s cloud environments:

  • Qlik Sense Enterprise for Elastic, for full management and hosting control.
    Multi-cloud deployment options are possible, on private and public clouds, and within the Qlik Cloud Services solution.

    • Kubernetes: It supports many clouds such as Google Cloud, Azure, and AWS.
      With the AWS marketplace as an example, Kubernetes enables AWS users to get Qlik’s analytics platform, associative engine, and powerful AI. They are then able to run their business analytics directly in the cloud via AWS. This offer allows them to deploy business intelligence in SaaS mode, move analytical tasks, or implement real-time data integration. They also have access to certifications such as APN AWS Technology Partner, AWS Data & Analytics Partner, Amazon Redshift Ready, and AWS Migration Competency.
    • Qlik Cloud Services, the public cloud environment hosted by Qlik, provides the latest functionality.
      Qlik Cloud Services secures your data with encryption of all traffic and customer data, GDPR compliant services, and SOC2 compliance. To store your data, you can choose between 3 data centers (US, Europe and Australia).
  • Qlik Sense Business, the cloud BI of 3rd generation. As previously stated, Qlik Sense Business allows all users to benefit from Qlik Sense Enterprise’s functions. In a strategy of accessibility and transparency anchored in Qlik’s SaaS-first policy. This solution becomes the first to make available to companies of all 3rd generation analytics services, with Qlik’s associative indexing engine.

Qlik wants to highlight the advantage of the cloud in its BI software services. In addition to the offering’s innovation and modernity, these cloud-first and multi-cloud solutions make it much easier for its users to do business.

Qlik Sense Business offers a more advanced analytical experience than previous offerings, with, in addition to the associative engine, the proposal of automated suggestions, the interactivity of dashboards, intelligent search, ability to connect to more than 40 different data sources, access to personal space, access to five shared spaces, a hub to facilitate sharing and management, a new management console and a MyQlik portal.
The cloud-first in order to offer analytics to everyone.

 

3- Advantages and disadvantages of the cloud

But why do companies prefer to migrate their data to the cloud?
We will now see the real benefits of this solution but also the disadvantages it can bring.

Advantages of the Cloud:

  • Centralized data: The cloud allows you to gather all your company’s data in one place, avoid the loss of information, and then allow a total picture of your company.
  • Reliability: By allowing constant analysis of integrated data even if it comes from different sources. Dashboards and reports will be enriched with real-time data.
  • Scalability: With the cloud, you can acquire new services according to your business needs. And conversely, you can stop using these services if you no longer need them.
  • Security and governance: All cloud solutions come with built-in security. Governance depends on each offering. It is important to pay attention to it to allow your users to access the data they need while ensuring transparency and accountability.
  • Speed of deployment: An analytics cloud is very quick to set up because it requires no third-party installation.
  • Maintenance: Cloud solutions are regularly updated, and new versions are developed to provide users with the best possible experience and unique innovation. These updates then allow companies to save on server maintenance costs.
  • Cost reduction: A reduction first of all on the on-site servers and their installation and, as said before, on their maintenance.

 

Disadvantages of the cloud:

  • Ecological: the cloud consumes a lot of energy and contributes greatly to global warming.
  • Public networks: the public cloud can be riskier in terms of security and data protection.
  • Network: Users of cloud solutions become dependent on the network’s state and can suffer losses if the network is down.
  • Data loss: If an accident occurs at the company’s cloud solution provider, the loss of data can be significant and greatly impact the company.
  • Laws: Cloud solutions can raise legal questions about data location. Which laws apply for which country?
  • Ownership: It is not always possible to export data, which raises proprietary lock-in if the company wants to change providers. A second issue can arise with the agreement to provide data to a third party and to oblige trust in that provider.

 

4- What to consider before choosing a cloud analytics platform

Today there are many solutions proposed in terms of cloud analytics, and it can be complicated to choose the right one for your needs.

Let’s look at the points to analyze before making this important choice.

  •  Truly cloud-based: Some solutions claim to be on the cloud but require local software. The cloud protects copies of data possible on local storage.
  • Third-party data integration: Some solutions do not offer third-party data integration. It is usually easy to use financial, demographic, weather data to develop deeper analysis with a cloud analytics solution.
  • Self-service and accessibility: Without being an IT expert, you must have quick and easy access to your data information. It is also important to choose a service that allows you to explore all the data analysis possibilities without restriction.
  • Governance: The chosen cloud solution must allow you to give access and modify it to the right people according to their needs and functions to ensure your data’s security.
  • Share on all your devices: You must choose a cloud adapted to your needs and your devices too. It is best to choose a solution that allows you to share its services on a computer, tablet, and phone.

 

Conclusion

The fire in Strasbourg of the OVH premises on February 2021, and consequently, the thousands of sites made unusable, shows us the cloud’s disadvantage.
The loss of certain data and business turnover is an important point. It raises questions about protection and security.

In the world of the cloud, all our data is flying away so as not to clutter us up.
But then out of our sight, out of our supervision.
Aware of the possible risks, it is now important to protect your data and opt for more secure solutions.
The solution of a multi-cloud strategy appears more reassuring, by protecting your data at several hosts you limit the risk of accident and loss.
This question raises data governance and defines in which cloud the data will be located, who will have access, and how.

The cloud, and more precisely the BI cloud, is continuously being developed and innovated to offer more efficient services to its users.
Security is at the center of the discussions concerning the deployment of a cloud solution.
It is also the point that will be reinforced more and more by cloud service providers to propose a reliable and sure service so that the data are not lost or hacked anymore. The user does not have any more fear concerning the confidentiality of his data.

 

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