Business Intelligence Analyst Gartner Income – Alibaba Cloud was named a Challenger in this year’s Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms.
Hangzhou, China, July 4, 2023 – Alibaba Cloud, the digital technology and intelligence backbone of Alibaba Group, has been named a Challenger in this year’s Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms. Last year, the cloud service provider was listed as a niche player in the same report.
Business Intelligence Analyst Gartner Income
The Gartner report evaluates vendors of analytics and business intelligence platforms designed to allow users to model, analyze, share and manage their data. Automated insights, reporting capabilities and data visualization are among the 12 critical capabilities defined for this market.
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Alibaba Cloud’s Quick BI platform, evaluated for this report, is an intelligent business analytics suite that offers services including data exploration and reporting. Its features allow business users to visualize and explore data to make informed business decisions.
“Data-driven knowledge is becoming increasingly important to drive organizational strategy around the world. We are seeing growing demand for platforms with a full range of data management and analytics services, reflecting the benefits these capabilities can bring to businesses. Being recognized as a Challenger in this critical area is a great encouragement to us and we believe it reflects our ongoing efforts to improve the capabilities of the Quick BI platform.” said Selina Yuan, President of International Business, Alibaba Cloud Intelligence. “We look forward to further supporting our customers around the world as they seek new ways to unlock the potential of their data.”
Quick BI provides a simple, easy-to-use platform to produce analytics reports based on information such as customer retention rates, number of active users, and more. The platform supports custom dashboards that allow users to present their information in their preferred formats. It has been widely used in various industries, such as retail, Internet, manufacturing, media and finance.
One example is IJOOZ, a leading smart retail and food robotics company based in Singapore, which has leveraged Alibaba Cloud technologies to optimize its current business and IT infrastructure. Quick BI helped IJOOZ with its data analysis, exploration and reporting capabilities, enabling better, more data-driven decision making across the company.
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Source: Gartner, Magic Quadrant for Cloud AI Developer Services, Jim Scheibmeir, Svetlana Sicular, Arun Batchu, Mike Fang, Van Baker, Frank O’Connor, May 22, 2023
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This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Alibaba Cloud Computing Ltd. The term “business intelligence” (BI) dates back to 1958, when IBM researcher Hans Peter Luhn coined the term in an IBM Journal article.
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However, it took until the 1980s when decision support systems (DSS) became popular and by the mid-1990s BI began to emerge as an umbrella term to cover software-enabled innovations in performance management , planning, reporting, querying, analytics, online analytical processing, integration with operating systems, predictive analytics, and related areas.
The 2014 Gartner Magic Quadrant shows the key players in the BI market. Different players differentiate themselves based on five abilities: ability to handle large volumes of data, ability to handle data velocity, variety (structured and unstructured), visualization capabilities, and domain/vertical specific accelerators.
The analysis is becoming three different markets. First of all, there’s the BI market, which is actually going through quite a few changes. This is a more consolidated market than we’ve seen in the past, and there’s a tremendous amount of work being done by Oracle, SAP, IBM and others to retool it for the next generation of BI. It is therefore a growing market, with many updates, new platforms, modernization requests and many customers who are finally realizing that the tools (visualization, etc.) are ready to provide them with some of the functionality they have historically relied on worry.
The second part of the market is what is called Advanced Analytics. In this case you need PhD-level data scientists with experience in machine learning, industry-specific domain modeling, and different types of data science who can apply them in a very specific way to industry-specific problems. This is a rapidly growing part of IT services. Additionally, there aren’t enough data scientists available.
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The third part of the market is Analytics as a Service. It’s about leveraging Software-as-a-Service platforms rather than on-premise ones. This is a business model that is more similar to Business Process Outsourcing (BPO). Customers buy business outcomes; they don’t buy transactions and FTEs.
The analytics market has thousands of boutique consultants who specialize in particular industries or specific technologies. It includes all the major technology providers, who are all trying to advance their business and the capabilities they are bringing to market. And then there are vendors who are simply bringing the highest capacity data science skills to the market and coming at it from a completely different angle, basically just renting the skills of their data scientists to the market.
The market is incredibly fragmented. We are in the early stages of market growth. Each of our customers is building this capability internally and is looking for more services from vendors, because the opportunity to apply analytics is in every single function, whether it’s customer analytics, industrial internet, e-commerce platform, It is growing . Analytics is embedded into literally every single business interaction.
More recently, to support a new generation of cost-cutting and growth initiatives, companies are investing heavily in obtaining actionable insights in near real-time (historical and predictive) and from a mix of disparate spreadsheets and myriad systems (legacy, internal silos, comparison customers, suppliers, partners, etc.).
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Another way to look at BI is the types of questions asked and answered. The simplest model developed by TDWI is shown here.
According to a Gartner report, the BI, analytics and business performance management software market grew 16.4 percent in 2011 to $12.2 billion in 2012 and $14.1 billion in 2013.
Companies are investing in software platforms to answer 3 critical performance questions: How are we doing? Why? What should we do?
This category is expected to have robust growth as BI and Analytics are considered the #1 priority. 1 in enterprise IT. New growth is also coming from Big Data: integrated devices such as Oracle Exadata, IBM Netezza, SAP HANA, EMC GreenPlum. I also see explosive growth in industry-specific analytics categories like predictive analytics/retail customers.
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BI platform software sales totaled $7.79 billion. Gartner identified SAP revenues at $2.88 billion, up 19.5% from 2010). SAP is the market share leader in BI, analytics and PM software. In second place is Oracle, with $1.9 billion in 2011 revenue, which, along with third-place SAS Institute ($1.54 billion in 2011 revenue), has seen a decline in market share. IBM reported $1.47 billion in software revenue in 2011 and 12.1 percent market share coming in fourth place, while Microsoft totaled $1.05 billion in 2011 with a consistent market share of 8 percent. ,7%.
IBM’s market share (through acquisitions) is definitely increasing as it accelerates its rapid acquisition strategy to penetrate the market: Cognos, Netezza, SPSS, ILog, CoreMetrics, Algorithmics, OpenPages, Clarity Systems, Emptoris, DemandTec (for Retail). IBM also has other complementary assets such as Watson, DB2 etc. They are building formidable capability around the value chain:
. They see this as a $20 billion opportunity in managing data, understanding it, and then acting on it.
According to the Gartner report, the Big 5 vendors (SAP, Oracle, SAS, IBM and Microsoft) continue to dominate, owning 68% of the market share. In the BI platform and CPM suite segments, they hold nearly two-thirds of the market share, while in pure statistical and analytical applications, SAS dominates the market.
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There is an ongoing consolidation of BI tools (visualization, ETL, reporting, data warehouse) across IT departments, while, at the same time, a new wave of data visualization tools and lighter-weight analytical applications is proliferating across lines of business units. In-memory and Mobile BI are two new, rapidly growing categories. We have seen tremendous customer interest in iPad-based analytics (CxO analytics).
Business users care less about who they buy from; they want easy-to-use, domain-specific features and speed to market. Business users don’t want long deployment cycles. Growing frustration with the performance, availability and latency of BI applications is driving a wave of investment in purpose-built data appliances like Oracle Exadata.
Gartner analyst Dan Sommer noted that the growth reflects the adoption of an “information-driven” approach. “It is clear that BI continues to be a technology at the heart of information-based initiatives in