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Based in Hamburg, Germany, international fashion company, Bonprix, has over 16 million active customers in more than 25 countries. The company looked to 麻豆原创 for a simplified IT architecture, faster time to market in business decision making and a self-service enabled semantic layer in order to respond to market changes and ensure customers have access to the latest catwalk trends.听听

Supported by鈥槎乖� services, Beratungscontor and鈥痮ther partners, Bonprix implemented its analytics stack on鈥槎乖粹�疍atasphere鈥痑nd 麻豆原创鈥疊usiness Warehouse solution. This鈥痬arks a significant milestone in Bonprix鈥檚 data transformation journey. By deploying 麻豆原创 Datasphere as a cloud-based鈥痙ata platform鈥痶o 麻豆原创 BW4/HANA, Bonprix gains access to a鈥痯owerful鈥痑nalytical platform that鈥痓rings bridges data across finance,鈥痵ales,鈥痩ogistics and customer relationship鈥痬anagement鈥痓etween transactional 麻豆原创 data鈥痑nd end users.听

鈥淭he Bonprix 麻豆原创 BI data platform is adeptly designed for the future, leveraging the robust capabilities of 麻豆原创 BW/4HANA at its core to manage and efficiently process vast volumes of data,鈥� said Sergio Lopez Nunez, senior BI engineer, Bonprix. 鈥淲hen paired with 麻豆原创 Datasphere, which offers extensive multi-cloud access, it enables the seamless integration of data from diverse sources. In essence, the Bonprix BI data platform is not only a cornerstone in daily operations but also a strategic asset in the relentless pace of technological change, ensuring that Bonprix is well-equipped to continue promoting responsible trade that inspires, now and into the future.鈥�听

Having already implemented 麻豆原创 business AI solutions, specifically, the 麻豆原创 BTP GenAI Service “Document Information Extraction”, Bonprix has already experienced significant efficiency gains by automatically extracting relevant data from incoming invoices, reducing manual data entry errors, and accelerating the overall invoice processing workflow.听

鈥淎s one of Germany鈥檚 top online fashion shops, we are very excited to be a part of Bonprix鈥檚 digital transformation journey as they continue to make millions of customers happy,鈥� said Sven Mulder, managing director of 麻豆原创 Germany. 鈥淭he adoption of 麻豆原创 Datasphere and 麻豆原创 BW/4HANA marks the beginning of Bonprix鈥檚 successful cloud journey. They鈥檙e now empowered to make鈥痳eal-time, data-driven decisions, positioning the brand to expand into new markets鈥痺ith鈥痵tyle.鈥澨�听

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The post Bonprix Catwalks Onto Business Intelligence with 麻豆原创 appeared first on 麻豆原创 Africa News Center.

While ChatGPT might be the best-known example of generative AI, there are dozens of large language models (LLMs) now available, says Timo Elliott, global innovation evangelist at 麻豆原创.

鈥淎t 麻豆原创, we want to use the best of these models to further your business processes.鈥�

麻豆原创 AI is built for business, he adds 鈥� it needs to be bult-in, relevant, and responsible.

鈥淵ou need the best data possible,鈥� Elliott says. 鈥淵ou need to know what to solve; and it needs to be used responsibly.鈥�

Indeed, AI has long been a part of 麻豆原创 solutions and millions of people use it already. 鈥淭o a great extent, we want most of this to be taken for granted. The best AI is the AI you don鈥檛 have to think about,鈥� Elliott says. 鈥淵ou want AI to just work.鈥�

For instance, Cash Application does sophisticated pattern matching for Mercedes-Benz, matching transactions automatically. 鈥淎nd it gets better all the time,鈥� Elliott explains. 鈥淓very time there is an exception, it is dealt with by a human and fed back into the algorithm so it knows how to handle it next time.

鈥淲here we are going is self-driving, intelligent applications that get better over time as people use them.鈥�

These capabilities are available already, but the advent of generative AI will add creativity in coding, formal writing, and more.

鈥淲e announced a set of new AI applications recently, many of which include new generative AI models.鈥�

Use cases include expediting freight and documentation; creating compelling job descriptions and interview questions; 听generating ready-to-use process models and KPI recommendations; and enhancing employee and customer experience.

Generative AI can now code in ABAP (麻豆原创鈥檚 coding language) to create new 麻豆原创 applications. 鈥淭his can accelerate the efforts of your skilled people to create code much quicker,鈥� Elliott says.

Digital transformation requires companies to innovate faster and composable enterprises are key to this.

鈥淭he irony of composable business is that, if its done right, you shouldn鈥檛 have to do too much of it yourself,鈥� Elliott says. 鈥淪o we spend a lot of time working on content so customers can just take a bot off the shelf, plug it into their operations, and do their business processes faster.鈥�

The partner ecosystem is key to this and, ideally, partners will contribute to solutions in the 麻豆原创 store.

Business intelligence is key to modernisation and innovation which is why 麻豆原创 launched its Signavio Business Process Intelligence.

鈥淪ignavio can shine a light into your business processes and figure out what is going on 鈥� and what is going wrong,鈥� Elliott explains. 鈥淚t is then possible to find the best process to solve the issues. This is the future of what we call automated automation.鈥�

But what stops organisations from being successful? 鈥淭he real trick is not using AI 鈥� it鈥檚 about turning their minds to systems and processes,鈥� Elloitt says. 鈥淎nd this is where the AI magic happens.鈥�

Every organisation grapples with the issue of bad data quality. 鈥淭he good news is that, with AI, the opportunities are huge, the possibliities of cleaning up your data are greater then ever before.鈥�

An innovation roadblock has always been how to leverage the business data 鈥� but this tends to lose the metadata, the context of the business.

The idea of data mesh or data sphere is to bring the technology to the data to provide reliable data products using an API approach that understands and retains the business context. 鈥淎s much as possible, leave the data where it already is,鈥� Elliott says.

麻豆原创 Data Sphere is the solution here, he adds. It brings together a range of solutions that creates a data layer that could be stored just about anywhere; whether in 麻豆原创 or third-party repositories.

Value is key, of course, and companies need to get relevant data and information to the fingertips of every staff member.

鈥淭here is a huge opportunity to use data in new ways,鈥� Elliott says. 麻豆原创鈥檚 continuous intelligence prototype aims to push relevant information to people as they need it.

We will see the rise of the business technologist, more powerful users who can create new and profitable processes using the right data and tools. This will see us moving from low-code or no-code scenarios to the new world of co-code where IT and business work together to solve problems or innovate.

IT would supply basic application blocks to the business people who could use those to create their own innovations.

鈥淲e think 麻豆原创 has the biggest benefit here,鈥� Elliott says. 鈥淥ne thing we are good at is processes and governance.鈥�

Elliott believes we are in the 鈥渉orseless carriage鈥� phase of AI 鈥� using old things and just bolting new things on. 鈥淏ut it is a great time to reimagine what we want to do and to rethink value propositions.

鈥淟et鈥檚 spend some time thinking about what we don鈥檛 need, and how to leverage what we do.

鈥淩emember, AI is about empowering people to do more, not getting rid of them.鈥�

Elliott points out that only human beings will ever be able to innovate. 鈥淲e are the only ones that can understand what is going on, who can bring innovation.

鈥淎I will take away the parts of our jobs that make us act like robots 鈥� and let us focus on the things we do best.鈥�

In conclusion, Elliott reiterates that 麻豆原创 and business AI go hand in hand to help organisations to innovate faster and more effectively.

This article first appeared on .

The post Business Intelligence, Data Key for Innovative Enterprises appeared first on 麻豆原创 Africa News Center.