Interpreting the most authoritative report of BI Circle of business intelligence--gartner Magic Quadrant 2015 (1)

Interpreting the most authoritative report of BI Circle of business intelligence--gartner Magic Quadrant 2015 (1)

Source: Internet
Author: User

The market share leader in traditional bi is disrupted by new BI vendors. These new vendors have made more people a big data analytics user and created higher business value.

BI Market trends

The BI market is making fundamental changes. Over the past 10 years, most of the IT departments have led the investment in BI projects, which are highly controllable, centralized and it-led. The IT department is responsible for compiling production Reports and then pushing it to consumers and analysts. Today, a large number of business users are pressing for interactive analysis to gain data insight through deep analysis, and they have very limited it or data science skills. On the one hand IT departments need to meet more and more data discovery requirements, on the other hand they do not want to sacrifice controllability.

While there is still a need to guide business based on reporting, the most significant changes are kanehide, especially to meet the needs of the new Business-user-driven. These requirements no longer use traditional, it-centric enterprise-class platforms, instead of a centralized data discovery deployment, which is now ubiquitous in the enterprise. Gartner estimates that more than 1/2 of the purchase demand comes from Data-discovery-driven. This de-centric model gives more business users the ability to analyze data, as well as the need for a controllable, data discovery approach.

It was a 6-year shift. In 2014, the It-centric BI platform is increasingly being replaced by business-user-driven and interactive analysis projects. With the growing number of new projects, and the growing concern in the BI sector, it is hoped that the overall controllable demand will grow. The goal of this shift is to enable a wider range of users and more scenarios to gain access to data analysis capabilities.

Traditional BI vendors have struggled to meet the needs of these business users by packaging and integrating other products, but their pale imitations have not been recognised by the market and have yielded little success. They are also investing in next-generation analytics tools, but the product is not fully mature (e.g. SAP Lumira and IBM Watson Analytics).

The demand for Embedded bi is growing fast, and users of various applications can benefit from BI by embedding analytics applications.

As enterprises build BI platform through Shuangfeng and controllable data discovery method, many business users want to access the data source controlled by IT department in self-service mode, which introduces complex data modeling tools that can be used by commercial users. They also want a quick and easy way to find relevant patterns and improve data insights. The current trend is to extend the application of data analysis, especially through deep analysis, to the wider access of users, especially non-traditional bi users, based on cloud deployment and support for various mobile devices.

The focus on cloud bi has fallen from 45% in 2013 to 42% in 2014. The main market for cloud bi comes from private clouds and the use of data in public clouds. While most bi vendors have their own cloud strategy, they can't integrate cloud services with offline deployment.

We see a lot of data analytics that need to integrate multi-structured data from both internal and external. For BI vendors, the integration of online and offline, multi-structured, streaming data, has become a very important function. Analytics based on stream computing and multi-structured data are mostly from early adopters, but these features are becoming more important.

Bi Magic Quadrant

Figure 1.Magic Quadrant for business Intelligence and Analytics platforms (BI Magic Quadrant)

Source:gartner (February 2015)

Bi Vendor Targeting overview

The 2014 was another challenge for the BI giants. There is a strange phenomenon, it-centric bi platform features rich, but user use is very limited, often only use the reporting. The Business-centric bi platform (Tableau, Qlik) has limited functionality but is widely used by users. Even reporting's features, which they are not good at, are also widely used, mainly because they are simple to deliver and extremely easy to use.

The current bi market looks like the mainframe/workstation market in the late 80, when customers and needs are undergoing a radical transformation. These changes have driven HP to thoroughly rethink and redesign the strategy and architecture of the computing platform. In the end, this shift has left Dec dead, because his actions are too slow. Similarly, today's bi giants are also standing in the middle of a crossroads.

While the data Discovery BI platform is considered an important complement to the It-centric BI platform, most of the new analytics projects have procured the former rather than the latter. This leads to a large user base of traditional bi manufacturers are being gradually marginalized, they can not provide competitive products, it will not be able to maintain growth.

While not the mainstream of development, we see more and more case for replacing existing platforms with products such as tableau and qv, especially for small and medium-sized businesses (I also include departmental applications). The Gartner survey found that more and more enterprises are inclined to deploy data Discovery BI on a larger platform scale, but they find that these products are still lacking in terms of enterprise-level monitoring, management, scalability, and so on, business-centric BI vendors are continuously complementing these capabilities.

If we start to see a large-scale shift to business-user-centric BI vendor replacement, the market shift is obvious. For now, a large number of buyers seem to be trying to wait and see if their it-centric BI platform complements the data discovery functionality, and these data discovery capabilities meet their needs. After all, if no bi vendor can do the same, the two segmented bi systems will pose a challenge to the business from monitoring, scaling, and support.

2015 is likely to be a key year in which democratization data analysis will dominate market demand and demand for regulation is also increasing. Next-generation data analysis capabilities are more important, such as supporting deep analysis while hiding complexity (data preparation, automatic mode search). In 2015 and in the future, the impact of these features on procurement will determine who will emerge as the leader in this market transition.

Supporting a large number of diverse data has become the mainstream demand in the BI market. At the same time, the integration of decentralized business-user-led application deployments and centralized enterprise application deployments has become a major challenge for bi vendor. The BI platform supports cloud data, streaming data, and multi-structured data, as well as social and network analysis, sentiment analysis, and machine learning. New challenges and opportunities come from the integration and management of these multi-source data to generate business value.

For the domestic market, I have observed that more and more enterprises want to appear business-leading, high-performance, and also have big data analysis ability of BI products. Domestic agile Bi started late, I created the Yonghong bi and peer succession of different data visualization analysis products, technology has been inferior to foreign counterparts, and has begun to go beyond the international competition in Big data analysis, exploratory analysis and other fields, and such as complex reports, data reporting and other domestic characteristics of the demand has been well resolved Of course, the local team's product service can bring better support and customer experience.

Another problem in the domestic market is that some enterprises, especially small and medium-sized enterprises, have not yet established a correct understanding of the data, do not know the true value of the data, or how to guide the operation and business through data, which requires a medium-to long-term cultivation. On the other hand, we also see that in addition to large institutions and large enterprises, many SMEs are very clearly aware of the value of data analysis, has a very strong desire to establish an effective data-based operation system, they are widely distributed in e-commerce, finance, and so on the pan-Internet industry. These enterprises are in a transparent and fully competitive market, leading more industry more enterprises development.

I believe we will see more and more enterprises to build a suitable data analysis platform, fully explore the value of data, quickly grow into the industry leader.



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Interpreting the most authoritative report of BI Circle of business intelligence--gartner Magic Quadrant 2015 (1)

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