Self-service Business Intelligence Tools: A Deeper Dive Right In To Gartner Magic Quadrant Approach

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Self-service Business Intelligence Tools: A Deeper Dive Right In To Gartner Magic Quadrant Approach – Do self-service BI tools support data governance, integrated data security, and organizational IT standards and policies? In some cases the answer is no. However, that shouldn’t stop you from looking into self-service BI tools. The question is not whether data management integrity can be maintained when using self-service BI tools. The question really is ‘which vendor should I choose to achieve true self-service BI and democracy without compromising data governance and security?’

So-called Self Service BI tools provide ready-to-use data connectors and access for business analysts or dashboard developers to connect to data sources and make discoveries using data visualization and discovery tools. Members of enterprise IT teams do not like to promote access beyond a select few developers and analysts because they fear it will breach data security mechanisms.

Self-service Business Intelligence Tools: A Deeper Dive Right In To Gartner Magic Quadrant Approach

Many of these popular BI tools, including Qlikview and Tableau, offer limited data security control options, or they require extensive development efforts to implement precise access rights. Their data discovery tools allow connecting to data sources from desktop discovery tools, and a select group of users can connect to the data they have access to (including data on their desktop or data collected from unverified sources) and they collect These users can perform data discovery, design dashboards, and make those packaged dashboards available to business users. Dashboards are published on the server and made available to business users in a browser environment with limited options and access to BI data for business users to analyze. Business users are often granted access rights at the control panel object level. In this way, IT cannot control access and distribution of data and compliance with data management standards.

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When an organization restricts or restricts business users’ access to BI tools, it cannot implement true self-service BI or provide true analytical and deep-dive capabilities. Business users are limited to “corporate” packaged views of the control panel, with limited drill-down and filtering capabilities. When it comes to the true democratization of data, these users are left out in the cold.

If your business users use their skills and knowledge to support the growth and success of the organization, the enterprise must find a way to link data management and security with self-service BI so that both corporate interests are met.

ElegantJ BI provides an IT security layer for creating and managing access to data sources and managing precise access rights to data in the semantic metadata layer, including access control on columns and column data levels. It also provides access control at the individual BI object level. For example, a single sales dashboard can be designed with line-of-business (LOB) or region-level access rights, thereby providing business users with access to relevant information based on their job function. This approach reduces development time because developers do not need to design different panels for different regions or LOBs. At the same time, the IT team can manage access rights at granular levels down to the column level, for example, region, sales volume or profit, and column data levels, for example, western region, production department, etc., without granting direct access rights. to source data to all users.

True self-service BI tools can support business user access and deep-dive analytics, as well as true access to comprehensive enterprise data, providing IT team confidence in data and security management. Get your business users out of the cold and give them true self-service BI tools, while giving your IT team a warm and fuzzy feeling by providing excellent data management and security.

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Karthik Patel is the founder and CEO of Elegant MicroWeb. Domains of expertise are in enterprise software applications, business intelligence, enterprise performance management, and enterprise governance through technology.

We continuously strive to build and enhance our partnerships and customer network around the world to deliver technology value through our software products and services.

ElegantJ BI is the flagship product of Elegant MicroWeb, with a unique memory-managed computing UI engine and “Design Once, Use Anywhere” that offers a seamless experience for Deep Dive Analytics across devices – Desktop, Tablets, Mobiles. Your organization consumes a lot of information that helps you understand the nuances of your industry. However, the traditional analytics model that deals with business data is slow, rigid and expensive. Modern enterprises require a modern approach to business intelligence that can be both managed and scaled according to their needs.

Enterprises are increasingly moving to self-service analytics and reporting tools, such as , for a long-term approach that meets the needs of both business and IT functions. Businesses need constant access to information to make decisions. They should promote analytical culture. Self-service analytics tools offer several important features that make data analysis easier, faster, and more accurate.

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The traditional way of dealing with business data isolates the analysis to a specific group of people who are responsible for reporting and monitoring the data. This inhibits the organization’s ability to make critical business decisions quickly.

For your data to be effective, the process from analysis to decision must be fast. The self-service analysis approach saves time at every stage of the work process, from installation to access, using intuitive panels and sharing information between organizational departments.

Traditional frameworks can take months to install, while self-service tools like , are quick to install and take just a few hours. It allows businesses to quickly and easily integrate information from multiple sources. It allows them to use in-memory capabilities to speed up information processing.

Visualizations reveal insights that cannot be identified in raw data. Without the right tools, gathering data and getting the gist of it can be tedious.

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Interestingly, it provides data visualization in a few simple steps. We enable companies to identify inconsistencies and patterns in data without spilling the beans.

Users can use data representation by entering information and generating interactive dashboards. The core of self-service analytics tools is the collaboration between business and IT. The result is a secure domain managed by IT that not only reinforces the authenticity of the organization’s data, but also empowers individuals to answer key questions.

Data is always growing in size and variety. Traditional BI believes that data should be fed into integrated data stacks. Modern BI tools accommodate different types of data collected from different sources in an organization.

Current BI tools allow you to combine semi-structured, relational and raw sources without expensive integration. It supports fine-grained management of your data sources and allows users to control and scale metadata to provide a single source of truth for all. The end product is a simple, hassle-free, user-friendly system that allows users to analyze information without knowing the intricacies of information storage. is a system that provides analytics management as a service for deep and multi-dimensional data analysis.

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Traditional BI systems hinder collaboration. With self-service analysis tools, you can quickly modify and update dashboards with simplified commands. Sharing is made easier with live dashboards that can be viewed in a web browser or installed in cloud applications.

New and improved data analysis tools allow users to insert their own evaluations, create new groups, sets, and boundaries, filter data into hierarchies, and assign subusers. With metadata organized in this way, users can easily share information and collaborate in real time.

Organizations must implement some kind of harmony between data availability and security. They need to standardize their data structures and adjust them as the business grows. Traditional data factories allow strict restrictions on data and reports, restricting access only to specific groups.

Modern analytics tools see data management as an important step in creating a reliable environment for self-service analytics that results in accurate, accessible, and measurable reports.

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Data is knowledge, and when people are equipped to ask and answer questions using data to make decisions, it can open up endless possibilities.

This is where analytical culture comes into play. To fully establish this, the company must integrate its two most important functions – people and IT. By giving employees access to information in a secure, IT-managed environment, it empowers individuals to realize the full potential of the business.

With self-service analytics, companies don’t have to sacrifice control. Instead, the former creates a structure between IT and business with a focus on fulfilling a common goal through people, processes and innovation.

With a modern approach to enterprise analytics, IT and business collaborate. IT creates a trusted environment for data and enables businesses to understand, analyze and find relevant answers to questions.

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Associations that use information to make decisions can better understand their customers, take advantage of opportunities, and gain a competitive advantage. Associations that have effectively adopted self-service analytics have achieved it through executive sponsorship.

A McKinsey global study found that organizations with high-quality analytics programs are more likely to win CEO sponsorship for their analytics initiative. By sponsoring an analytics initiative, leaders can help their enterprise transform.

At the heart of the analytics culture is a self-service analytics platform that enables the entire organization. It’s instinctive

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