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Top 10 Business Intelligence Certifications

From BI analysts to BI directors business intelligence pros are in high demand. Here are 10 certifications



10 business intelligence certifications and certificates to advance your BI career

From BI analysts and BI developers to BI architects and BI directors, business intelligence pros are in high demand. Here are the certifications and certificates that can give your career an edge.

As data becomes increasingly vital to business success, business intelligence (BI) continues to grow in importance. And with a strong BI strategy and team, organizations can perform the kinds of analysis necessary to help users make better data-driven business decisions.

BI encompasses numerous roles. BI analysts, with an average salary of $73,705 according to PayScale, provide application analysis and data modeling design for centralized data warehouses, and extract data from databases and data warehouses for reporting, among other tasks. BI developers, with an average salary of $86,190, work with databases and software to develop and fine-tune IT solutions. BI architects, earning on average $114,798, analyze and implement BI for their organizations, with responsibilities that range from determining platforms to building and maintaining data warehouses. And BI directors, on an average salary of $128,148, lead design and development activities related to the enterprise data warehouse.

In its 3Q 2023 IT Skills and Certifications Pay Index report, research firm Foote Partners notes that the average pay premium for tech certifications was down 0.7%. In general, Foote Partners’ statistics show that while organizations will pay a premium for certifications, they’re more willing to pay for non-certified skills, especially in areas like prescriptive analytics, AI skills, and generative AI skills. Over the last two years, the average value of IT certifications has fallen more than 1%, while the value of noncertified skills has risen by a similar amount. The median pay premium for noncertified skills is now more than 9.5% above base salary, while that for IT certifications is 6.5%.

Certifications are not required to work in BI, but they may provide an edge by showing employers you have the right skillset. Below is our guide to some of the most sought-after BI certifications.

Top 10 Business Intelligence Certifications

  • Google Business Intelligence Professional Certificate
  • Certified Business Intelligence Professional
  • IBM Data Analyst Professional Certificate
  • Microsoft Certified: Power BI Data Analyst Associate
  • QlikView Business Analyst Sense Business Analyst
  • SAP Certified Application Associate: SAP BusinessObjects Business Intelligence Platform 4.3
  • SAS Certified Specialist: Visual Business Analytics
  • Tableau Certified Data Analyst
  • Tableau Desktop Specialist
  • Tableau Server Certified Associate

Google Business Intelligence Professional Certificate

This certificate consists of a three-course series: Foundations of Business Intelligence, The Path to Insights: Data Models and Pipelines, and Decisions, Decisions: Dashboards and Reports. Intended for people with some experience with analytical principles, it focuses on teaching students and improving their knowledge with extracting, transforming, and analyzing data to meet organizational goals, and creating dashboards and designing data visualization graphs and charts. The courses are online and Google estimates students can complete them in less than two months at 10 hours a week.

Certified Business Intelligence Professional (CBIP)

The CBIP certification program is intended for senior-level personnel in the information systems and technology industry with a focus on data management and business analytics. The cert demonstrates that you’re up-to-date with BI technologies and are knowledgeable about best practices, solutions, and emerging trends. It also has four specialty areas to choose from: leadership and management, business analytics, data analysis and design, and data integration, and requires passing three mandatory multiple-choice exams — your choice of the Information Systems Core or Business Core Exam, the Data Foundations Exam, plus at least one specialty exam (Business Analytics, Data Integration, Data Analysis and Design, or Leadership and Management). Each applicant is given 90 minutes to complete each 110-question exam. The initial certification is valid for four years and must be renewed every three years thereafter. Recertification requires proof of 120 credit hours of continuous education earned since the last renewal, and an annual fee of $125 every year after the first.

IBM Data Analyst Professional Certificate

The IBM Data Analyst Professional Certificate is a beginner-level credential to demonstrate proficiency in creating charts and plots in Excel, and working with IBM Cognos Analytics and Tableau to build dashboards for visualizing data. The certificate doesn’t require prior programming or statistical skills. Candidates work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, and Cognos Analytics. The certificate also requires nine online courses completed on your own schedule, culminating with a capstone project designed to showcase data analyst skills.

Microsoft Certified: Power BI Data Analyst Associate

The Microsoft Certified Power BI Data Analyst Associate certification equips candidates with a fundamental understanding of data repositories and data processes, both on-premises and in the cloud. They become subject matter experts who can design and build scalable data models, clean and transform data, and provide business value via data visualizations. The certification is intended for data and business intelligence (BI) professionals who use Power BI to develop reports and dashboards that visualize data in the cloud or on premises. The certification also requires passing the Microsoft Power BI Data Analyst exam, which measures a candidate’s ability to prepare, visualize, and analyze data, as well as deploy and maintain assets.

Qlik Sense Business Analyst

The Qlik Sense Business Analyst certification demonstrates your ability to identify requirements, design applications, prepare and load data, and develop applications. Candidates must have practical experience developing production-quality applications in Qlik Sense, experience creating dimensions, measures, and objects for the master library, understand UX and design best practices, and have experience building visualizations. The certification also requires passing a 50-question, multiple-choice exam in two hours.

SAP Certified Application Associate: SAP BusinessObjects Business Intelligence Platform 4.3

This certification demonstrates you have the skills and knowledge to design for, deploy, and run SAP’s BI platform, and that you can configure and manage servers in an SAP Business Intelligence platform deployment, as well as design and deploy an SAP Business Intelligence platform system. SAP recommends candidates combine hands-on experience and education courses to prepare for the required multiple-choice exam delivered by Pearson VUE.

SAS Certified Specialist: Visual Business Analytics Specialist

The SAS Certified Specialist: Visual Business Analytics certification is intended for analysts who use Visual Analytics to analyze data and design reports. It validates your skill in using SAS Visual Analytics to add and manipulate data items, analyze data, and design and share reports. It requires a passing score of at least 67% on the SAS Visual Analytics Using SAS Viya exam administered by SAS and Pearson VUE. The exam consists of 50 to 55 multiple-choice and short-answer questions, and the certification expires after five years.

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5 Ways Artificial Intelligence is showing Promise as a Decision Maker

CIOs are seeing payoffs from using Artificial Intelligence to automate myriad types of business tasks and workflows



5 ways AI is showing promise as a decision-maker

Artificial Intelligence holds immense promise not just in automating tasks but taking actions that deliver results.

CIOs and others in the C-suite are already seeing payoffs from using AI to automate myriad types of business tasks and workflows. Now they’re eyeing a next-phase opportunity—relying on machine intelligence to handle complex decisions.

“If you look at the advances we have seen in Artificial Intelligence, with the large amounts of data that large language models can process, we can safely hand off various decisions to machines,” says Prasad Ramakrishnan, CIO & SVP of IT at Freshworks.

AI is becoming an integral part of decision-making for many different business functions – from finance to manufacturing to sales. Here’s a look at a few areas where it’s gaining influence.

Chatbot conversations and decisions

By some estimates, intelligent chatbots can already answer 80% of routine customer questions. This reduces costs while improving customer experience. Instead of waiting on hold or navigating through phone menus, customers can instantly get answers from a virtual agent that is far more engaging and knowledgeable than past generations of chatbots.

“Chatbots can come to your rescue with an answer derived from a knowledge base and know what type of tone to use when responding,” says Ramakrishnan.

Companies are now moving toward AI-powered decision-making in customer service—tapping into voice and sentiment analysis to automate complex processes such as recognizing customer intent and taking a recommended action to resolve it.

Sales optimization

In sales, AI can provide account reps with the information they need to close deals. An AI system can gather data from customer relationship management software, social media profiles, email interactions, and purchase histories to identify the candidates most likely to convert.

It can also factor in data specific to a sales prospect, such as whether the person has downloaded a resource or engaged with a particular email message. AI can then guide sales reps to follow up on the most promising prospects.

“It can even feed into the sales narrative, prompting the rep to ask the right questions or use offers that have a higher propensity to appeal to a particular customer,” Ramakrishnan says.

Outcomes are fed back into machine learning models to improve prediction accuracy continually.

Dynamic pricing

Airlines, ride-sharing services, and online retailers have long used dynamic pricing to adjust to changing market conditions. Utilities are an advanced use case: Power companies use sophisticated algorithms to set prices dynamically according to the volume of electricity generated by renewable energy sources and demand at different times of the day.

AI makes this capability available to any business. For example, a retailer could adjust prices on its website based on the visitor’s identity, inventory levels, and competitor prices. Hotels could dynamically adjust room rates based on traffic forecasts, weather conditions, and events in the area.

Supply chain logistics

Optimizing supply chains is a daunting task because of the number of variables involved. AI can help every step of the way. AI-generated “digital twins,” or virtual representations of physical assets or systems, can replicate live scenarios and predict breakdowns.

AI analytics tools can assess supplier performance and capabilities to help companies choose the most reliable sources at the lowest cost; they can further streamline operations by using blockchain technology to execute smart contracts, in which transactions are automatically triggered when certain conditions are met.

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AI & Augmented Decision Intelligence: The Next Paradigm Shift in Hospitality Revenue Management



ai augmented decision making

Artificial Intelligence is everywhere. It’s making inroads into practically every field of human activity. It’s integrated into search engines, word processors, and various apps likely installed on your smartphone in your pocket. And there’s a reason for the tech’s proliferation: it is incredibly adept at analyzing data much faster and at a much larger scale.

In the hospitality realm, most people consider revenue management to be something that only humans can do effectively. Now, with the advent of AI, that’s no longer the case. As technology continues to advance, there is a growing trend toward enhancing, automating, and optimizing decision-making processes, even for complex and collaborative scenarios. This shift reflects the ongoing integration of AI technology to make decisions more efficient, accurate, and streamlined.

Indeed, a growing number of hotels and hotel chains have been looking to reap the rewards of an AI-driven revenue management system (RMS) to optimize their pricing strategies. However, just because a system bears an AI moniker in its marketing doesn’t suddenly turn it into a revenue management silver bullet. The truth is that legacy solutions have algorithms that were created before AI made its appearance, so they can’t be AI-first. These days, that’s a costly mistake.

Hoteliers should recognize the distinctions between a revenue management system just using buzzwords like AI and what a truly modern AI-first system will do when it’s well designed. FLYR’s solution is also designed to be user-friendly and intuitive. It presents complex data in a simple, easy-to-understand format, enabling hoteliers to make informed decisions quickly and efficiently.

We’ll look at why FLYR’s AI-first solution leads the RMS pack with its decision intelligence capabilities in a little more detail, but first, let’s take a deeper look at what decision intelligence is.

What is Decision Intelligence?

Decision intelligence (DI) is a multidisciplinary field that uses advanced techniques from data science, machine learning, and artificial intelligence to guide decision-making processes. In the context of hotel revenue management systems, DI can bring about a transformative change by enabling more accurate, data-driven decisions.

In the realm of dynamic pricing, DI utilizes comprehensive analyses of booking patterns, market trends, and competitor pricing to optimize rates strategically for maximum revenue. Its impact extends to enhancing demand forecasting and providing unparalleled precision for inventory control and staffing decisions.

DI refines guest segmentation by delving into data, allowing personalized services that elevate satisfaction and boost revenue. Furthermore, it guides strategic choices in distribution channel management, optimizing focus for revenue maximization. In addressing the perennial challenge of overbooking, DI’s predictive capabilities empower informed decision-making, minimizing the risks of guest disappointment.

Moving beyond conventional revenue management systems that offer decision support solely based on supply and demand cues, decision intelligence algorithms and models meticulously examine data to grasp price sensitivity. They can autonomously modify rates for specific rooms, nights, and lead times, providing a more dynamic and responsive approach.

Unlike other systems, FLYR algorithms are totally prescriptive, providing insights that would have otherwise flown under the radar – and delivering recommendations for sound decision-making to respond to data-based signals rapidly.

Historical vs. Real-time

A lot of customers of other “AI” RMS providers we talk to describe the challenges around the importance those systems place in historical data. These systems rely on historical data as the basis for their pricing and inventory recommendations, limiting the scope of those recommendations to past patterns and trends. This is less than ideal in dynamic markets prone to rapid shifts – historical data can lose its relevance rather quickly.

The algorithms used in decision intelligence continually analyze your hotel’s stream of data. They can make micro-targeted adjustments on room nights, providing an edge to revenue managers who can quickly respond to shifts in market conditions, which translates to enhanced profitability. That’s no small benefit when demand patterns fluctuate rapidly, such as in the hospitality industry.

In many of the older RMS systems, they typically have to run for a minimum of three months in order to generate useful recommendations. You really don’t get optimized results until you’ve been running the system for a year. In a next-generation system like FLYR, you can start getting optimized pricing and forecasting results as soon as a week after the system is connected. This is what differentiates the FLYR technology and is a true indication that it just works in a new and better way.

Automation & Scalability

With a fully automated pipeline, decision intelligence-capable systems are quite simply more efficient and less error-prone than legacy systems. The latter typically rely on rule-based approaches and manual analysis to spawn their inventory and pricing recommendations. Again, this slows down the process, and the resulting insights may well be out of date. And we all know that human intervention can introduce errors in the data, resulting in errors in the recommendations.

Case in point: a McKinsey study found that an AI-driven RMS could reduce errors by 20% to 50% and reduce lost sales by up to 65% – not a fringe benefit by any measure.

You may have noticed my use of the word “recommendation” when discussing other revenue management systems. That’s because these solutions typically provide recommendations rather than actionable insights. They make suggestions, but the final decision-making will hinge on human judgment, leading to the potential introduction of errors and biases.

They also struggle to handle the sheer volume and complexity of data available today. In contrast, FLYR’s solution automates these processes and uses AI to analyze data more accurately and efficiently. It is also scalable enough to grow your business without skipping a beat. The bigger your business, the more data it generates. So you’re going to want a system that won’t balk under pressure.

Other systems tend to be developed for specific hotel sizes or types and cannot easily accommodate changes in business needs or market conditions. FLYR’s solution is more adaptable and responsive to changes in the market. It continuously learns and adjusts its predictions and recommendations based on new data, ensuring that hotels are always equipped with the most up-to-date and accurate information. This is a significant advantage in the fast-paced and unpredictable hospitality industry.

Integrated vs. Siloed

As mentioned above, decision intelligence operates holistically. That means it integrates, among other metrics, booking patterns, market demand, competitor pricing, and guest preferences. So, it will require access to existing systems for optimal performance and to yield the maximum benefits. FLYR’s decision intelligence-enabled RMS is designed for easy, seamless integration with a plethora of existing systems. This enables hotels to leverage data from various sources in real-time, leading to more informed revenue and guest relationship management decisions.

With limited integration capabilities, legacy systems can’t consider many complex and interrelated factors that significantly impact revenue management. They cannot factor in external data points, like market demand, competitor pricing, and customer segmentation, limiting the insights they can produce.

Leveraging Decision Intelligence

FLYR brings together AI and intuitive workflows to deliver the first-of-its-kind AI-augmented decision intelligence platform. This is a paradigm shift for the hospitality industry, providing massive accuracy, efficiency, and profitability gains over legacy RMS systems.

Offering a trifecta of advantages, decision intelligence enhances predictive insights, optimizes pricing strategies, and refines guest segmentation. Recognizing that the effectiveness of any algorithm hinges on the quality of the input data, as the principle “garbage in, garbage out” aptly underscores, FLYR places a paramount emphasis on obtaining accurate and high-quality data, aiming for a standard of precision that surpasses previous benchmarks.

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Huawei Cloud: Accelerating Intelligence in Europe, for Europe

EMEA organisations expect cloud computing to improve productivity and expedite new product development



Huawei Cloud: Accelerating intelligence in Europe, for Europe

The Digital Future in Europe

The future of European organisations and industries is looking increasingly digital and cloud-centric.  According to Foundry’s Digital Business Study 2023, 91% of EMEA organisations have adopted or plan to adopt a digital-first business strategy. At the same time, Foundry’s Cloud Computing Study 2023 found that 71% of EMEA organisations are defaulting to cloud-based services when upgrading or purchasing, while 60% have been accelerating their cloud migrations over the past year.

EMEA organisations expect cloud computing to improve productivity, enable innovation and new product/service development, and upgrade legacy tech with lower total cost of ownership. 54% of IT Decision Makers also expect to use cloud capabilities to leverage Artificial Intelligence (AI)/Machine Learning (ML) over the next year, which many see as a potential game changer for their industries.

However, EMEA organisations are facing challenges in their digital and cloud journeys. 34% reported a lack of the right skill sets, while 29% cited complexity of IT infrastructure as a major hurdle. There were also concerns around data privacy and security, cloud costs, and compliance issues which would need to be addressed before organisations could reap the potential offered by the cloud.

Enabling Industries through Everything as a Service

To help European industries and organisations overcome these challenges and quickly enable cloud initiatives, Huawei Cloud has adopted a strategy of “Everything as a Service.” This comprises multiple tenets:

  • Infrastructure as a Service allows industry partners to rapidly scale their computing, network and storage across Huawei’s global access network, comprising 30 Regions and 84 Availability Zones across more than 170 countries
  • Technology as a Service makes available Huawei’s continuous innovation and leading-edge capabilities in cloud-native, Artificial Intelligence (AI) and data and media, offering organisations more flexibility and choice in their technology partnerships
  • Expertise as a Service taps on Huawei’s three decades of experience in ICT, as well as the best practices of its network of global partners

Leading innovation in cloud-native, data, and AI

Huawei’s answer to the growing demand for cloud-native as the platform-of-choice for digitalisation is KooVerse: Huawei Cloud’s distributed infrastructure of storage, computing, networking, and security resources, designed with a unified architecture on a globally accessible platform to help organisations leverage the latest in cloud-native services and technologies.

To that point, Huawei is the only founding member of the Cloud-Native Computing Foundation (CNCF) from Asia, due to its consistent investment in developing and improving cloud-native services such as Ubiquitous Cloud-Native Services (UCS), Cloud Container Engine (CCE) Turbo, Cloud Container Instance (CCI), and CCE AutoPilot. In the Netherlands, these services helped 433, the world’s biggest football community, improve production efficiency and reduce costs by 25%.

On the data side, GuassDB is the result of 20 years of experience developing databases. Huawei’s next-generation distributed cloud database is designed for high availability and security, performance and flexibility. GaussDB has been widely used in banking, insurance, securities, and energy.

Tailoring AI for Industries

Building on its “AI for Industries” strategy, Huawei Cloud designed Pangu pre-trained AI models, tailored for a range of industries including finance, government, manufacturing, mining, meteorology, and railways.

“Huawei Cloud Pangu models will empower everyone from every industry with an intelligent assistant,” says Zhang Ping’an, Huawei’s Executive Director and CEO of Huawei Cloud, “and help to reshape all industries with AI.”

In the field of meteorology, the Pangu weather model has become the first to achieve better precision than state-of-the-art numerical weather prediction methods, with a prediction speed several orders of magnitude faster. Consider how the Pangu model was able to predict a 10-day typhoon trajectory in 10 seconds against five hours using current methods. These ground-breaking results were published in the July edition of the scientific journal Nature. In pharmaceutical R&D, the Pangu drug molecule model has drastically shortened lead compound discovery cycles from years to a single month, while achieving a 70% reduction of costs.

Building Trust in the Cloud

Addressing a key concern for EMEA IT leaders, Huawei Cloud has more than 120 security and compliance certifications, including C5 certification with zero deviation. Huawei Cloud provides compliance consulting and security services, while Huawei’s Compliance Compass platform helps users ensure security and compliance.

To help build trust in cloud services in the EU, Huawei Cloud works with SCOPE Europe and EU Cloud CoC to contribute to the Third Country Transfers Module and GDPR Compliance Standards. Huawei Cloud has also released white papers to share its expertise on privacy protection, data security and cloud security, and is a Board Member of the EU Cloud Code of Conduct General Assembly.

Huawei Cloud sees stability and reliability as critical lifelines. Deterministic Site Reliability Engineering (SRE) offers service availability of over 99.99%, with recovery four times faster than industry average. In addition, Huawei Cloud offers a three-level support system, deploying five service teams in Europe, and a series of 24/7 support centers worldwide. 

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As a global cloud service provider, Huawei Cloud offers expertise and experience in digitalisation and globalisation, as well as ecosystem capabilities to help partners expand into global markets. A leading Chinese car brand

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