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Challenge

1. The IT infrastructure of Nissan Middle East FZE where the PowerBI Report Server platform was hosted was in an on-premise datacenter which was designed to be scalable and robust with multi node physical clusters including the server, storage and network components. However, most of the physical hardware was quite old and not equipped with the latest generation of physical servers.
2. Frequent hardware crashes and portal downtime kept troubling the availability of the PowerBI Report Server application. Assigning a touch hand support person to power on the hardware that was down seemed quite impossible due the restrictions during covid period. Hence, Nissan Middle East FZE wanted to look for another viable solution.
3. Though the hardware setup at Nissan Middle East FZE was well equipped to meet the occasional spikes in the traffic, it was observed that over a course of 6-month time, most of the IT infra was underutilized than predicted. It was realized that spending huge amount of money on an old hardware plus software maintenance, license costs, internet bandwidth, datacenter cooling and maintenance, touch support personnel and electricity costs – were keeping the business operations challenging.
4. There was an attempt by Nissan Middle East FZE to select a cost-effective solution that can host PowerBI Report Server application servers, web servers and archival data. This way IT infra can be re-provisioned to host sensitive data on-premise and the rest on the cloud, thereby reducing the overall physical hardware costs spent on a yearly basis.

Why AWS

1. Nissan Middle East FZE decided to migrate PowerBI Report Server, database servers and archival data to AWS.
2. The PowerBI Report Server’s AWS architecture includes Amazon Elastic Compute Cloud (Amazon EC2), that provides complete control of its computing resources, updates to tables in Amazon Relational Database Service (Amazon RDS) and AWS Elastic Load Balancer was used to distribute the traffic to the underlying EC2 instances based on the load.

Benefits

Nissan Middle East FZE uses AWS services to provision infrastructure and deploy the PowerBI Report Server platform to other departments within it. In addition, the PowerBI Report Server resources that are no longer required to be run all the time are made to auto shutdown thus saving cost. Nissan Middle East FZE reported a 28% cost reduction after implementation of AWS for the PowerBI Report Server platform.

The implementation of PowerBI Report Server on AWS made Nissan Middle East FZE confident in the security of its data, and its accreditation team is enthusiastic about the monitoring and auditing capabilities provided by AWS tools. With the implementation of IAM roles, Nissan Middle East FZE IT team was able to isolate systems and tightly control user accesses. These capabilities were harder to achieve within the existing infra but were available out of the box with AWS

By adopting AWS to host the PowerBI Report Server platform, Nissan Middle East FZE has been able to innovate and experiment to a degree previously impossible. For example, Nissan Middle East FZE compared the performance and cost-effectiveness of three different cloud solutions. Without moving to the AWS, the costs associated with running an outdated on-premise hardware would have creeped up and the alternative way of upgrading the existing on-prem infrastructure to the latest hardware models and then hosting the PowerBI Report Server application on top of it would have taken months.

What could be the Cloud computing trends to look forward to in 2023? Let’s have a look

1. Utilising Edge Computing
2. AI and ML Services
3. Disaster Recovery
4. Multi and Hybrid Cloud Solution
5. Cloud Security and Resilience
6. Cloud Gaming
7. Kubernetes and Docker
8. Serverless Computing
9. Blockchain
10. Metaverse
11. IoT

Let’s deep-dive:

1. Utilising Edge Computing

In the world of cloud computing, edge computing is one of the most popular trends. Here, data is evaluated geographically nearer to its source and stored and processed at the network's edge. As modern internet technologies emerged, the internet speed has helped in reducing latency, technologies such as 5G is used more frequently, and processing can be done swiftly. Greater privacy, quicker data transmission, security, and improved efficiency are just a few of the primary advantages of edge computing. Edge computing is expected to be at the core of every cloud strategy in 2023, making it the most important development in this area.

2. AI and ML Services

Two technologies that are closely related to cloud computing are artificial intelligence and machine learning. Due to the volume of data processed for the machine to learn patterns, this area demands faster processing and abundant storage requirements for training algorithms and data collection respectively. Due to the availability of virtually infinite computational capability, on-cloud AI and ML services are more cost-effective on the cloud. Cloud computing is used for handling enormous amounts of data to raise productivity at tech firms. Increased self-learning and automation capabilities, improved data security, and more individualised cloud experiences are the main trends that are most likely to arise in this fiel

3. Disaster Recovery

The ability to have a DR site in a geographically remote area helps to quickly restore vital services in the event of a natural or man-made disaster. It describes the process of employing cloud-based resources to recover from a disaster in the event such as power outages, data loss, or device failure/problems.

4. Multi and Hybrid Cloud Solution

Many businesses have embraced a multi-cloud and hybrid IT approach that mixes legacy platforms, on-premises, dedicated private clouds, and several public clouds. They provide a mix of public and private clouds tailored to the requirements of particular firms where several business drivers matter for instance like those of insurance, banks, etc. Multi-cloud and hybrid cloud solutions will thus be among the most popular cloud computing trends in 2023 and the years to come.

5. Cloud Security and Resilience

When companies shift to the cloud, there are still several security vulnerabilities. Investment in cyber security and building resilience against everything from data theft to the consequences of a pandemic to global trade will become more crucial and major variables in the coming years. The use of managed "security-as-a-service" providers, AI, and predictive technologies will increase in 2023 as a result of this trend to identify risks before they result in problems. Studies say that leading vendors of cloud computing invest over a billion dollars every year to protect their customers’ data.

6. Cloud Gaming

Cloud gaming platforms operate similarly to remote desktops and video-on-demand services; games are stored and executed remotely on a provider's dedicated hardware and streamed as video to a player's device via client software. It can be advantageous as it eliminates the need to purchase expensive computer hardware or install games directly onto a local game system. Cloud gaming can be made available on a wide range of computing devices, including mobile devices such as smartphones and tablets, digital media players, or proprietary thin client-like devices. Microsoft, Sony, Nvidia, and Amazon all offer video game services. But video game streaming requires more data and is only doable with fast internet. With the launch of 5G in 2023, the cloud gaming sector will grow significantly.

7. Kubernetes and Docker

The main trend is the growing use of container orchestration tools like Kubernetes and Docker. Large-scale deployments that are extremely scalable and effective are made possible by this technology. These are expandable, open-source platforms that manage services and workloads from a central location while running applications from a single source. Both platforms offer high scalability and efficiency. Over the following several years, Kubernetes and Docker will continue to play a significant role in cloud computing trends as they are developing quickly.

8. Serverless Computing

Because of the advent of the sharing economy, serverless computing entered the computing sector. Instead of being deployed on physical servers in this case, compute resources are offered as a service. This indicates that instead of needing to maintain its servers, the company only pays for the resources it uses. Additionally, serverless cloud solutions are growing in popularity because of how simple they are to use and how rapidly one can design, deploy, and expand a cloud solution. Overall, this technology is a trend that is just starting and is becoming more and more popular.

9. Blockchain

Blockchain, which users continue to follow more and more, is a connected list of blocks containing records. Blocks of data are stored using cryptography. It has outstanding decentralisation, security, and transparency. In conjunction with the cloud, it is currently utilised more frequently. It can securely and affordably process enormous volumes of data and regulate documents. For many industrial applications, the new technology is beginning to hold out a great deal of promise.

10. Metaverse

The days are not long for the Metaverse and cloud computing to become inextricably linked to each other. The metaverse will compel businesses to migrate to cloud infrastructures to host their virtual worlds. Massive amounts of workloads will be migrated, paving the path for even more innovations to model their virtual worlds. Considering the difficulties of building a metaverse without highly available and scalable premises and hosting grounds, the adoption of cloud computing will be inevitable. As more layers of complexity will be added to the metaverse as it matures, the need for a strong foundation to support the whole thing and to deliver a flawless user experience with no backend issues will arise. Consequently, cloud providers engaged in the metaverse will create metaverse-compatible solutions to assist businesses in quickly establishing their virtual space.

11. IoT

In the realm of cloud computing, IoT is a well-known trend. Connectivity between computers, servers, and networks is maintained by this technology. It performs the role of a middleman, guarantees effective communication, and helps gather data from distant devices. Due to the enormous data produced by IoT devices, it requires many terabytes of storage. Since the cloud, the storage of data has become cheaper. In recent years storing and processing machine-generated data has become relatively easier. In the coming years, businesses would be able to efficiently analyse data from IoT devices and make informed decisions.

Summing Up

Even though cloud computing has been present for more than a decade, its popularity has skyrocketed in recent years. Given this growth trajectory, cloud computing is on track to become the most discussed technology in 2023. Recent studies show that by 2028, the cloud computing market is anticipated to be worth more than $1 trillion. Being the game changer, its impact will grow along with the adoption in the coming years too.

Beinex Offerings

Beinex is all about transforming the way organizations work with data to bring out the best in Business, Technology and People. Our association with Snowflake, a leading cloud-first data warehouse service, is a partnership that we leverage to support the data analytics solutions that we offer our clients.

Most of the companies operating today are data-driven as they have started identifying the value of data. The value of data and data marketplaces are evolving with the growth of big data and data requirements of companies.

Data Marketplace

In simple terms, these are online marketplaces where we can buy and sell data of any sort. Data marketplaces offer several kinds of data from a wide range of different data sources. These data include Business Intelligence, demographics, research, and marketing data. Data types are structured and offered to clients by data providers. Providing buyers with more choice of high-quality data generates more engagement and encourages fair pricing between the sellers. Every company has the potential to earn revenue from the information it generates. In a recent study of more than 400 organizations, only 1 in 12 were monetizing their data to its fullest extent. Modern data monetization strategies can help you open brand new revenue streams. There are 3 key steps to monetize your data and drive new revenue streams.

Understand your Data Offerings - What types of data or data services are you producing that would be valuable to other organizations?

Decide How to Price Data Products - What should be the pricing strategy followed, and how easy would it be to put into action?

Know About Data Sharing Methods - Which distribution channel should be selected for data sharing that adheres to GDPR and data governance policies?

Once you have decided on the data offerings and priced the data products, the key to successfully monetize your data is by sharing the data with the clients/ prospects. The customers and business partners would be eager to get data from you, especially if you can make the process easy and secure. Traditional data sharing technologies often use FTP, Cloud Storage, or API. These methods generally do have few disadvantages.

1. Storage costs for both vendors and buyers
2. ETL costs and effort
3. Security vulnerabilities
4. Service and support costs
5. Latency and potential errors leading to poor customer experience

How do we overcome these challenges? There are platforms that make revenue generation easier with secure data sharing methodologies. Snowflake is one of the most secure and innovative platforms.

Snowflake & Data Monetization

Snowflake is an analytic data warehouse provided as Software-as-a-Service (SaaS). It provides a data warehouse that is faster, easier to use, and far more flexible than traditional data warehouse offerings. Snowflake allows companies to easily publish a variety of data sets that become immediately available for use or purchase for clients. Snowflake Data Exchange, a modern data sharing method, reduces the time to market and significantly influences customer success. Data Exchange is your own data hub for securely collaborating around data between a selected group of members that you invite. It enables providers to publish data that can then be discovered by consumers. The benefits of Snowflake Data Exchange over Traditional Data sharing Methods are:

1. Secure Data Sharing
   • Exchange data within your organization between different business units. Collaborate with external parties such as vendors, suppliers, partners, and customers.
2. Reduce Time to Market
   • Break down data silos and reduce time to market.
   • Interchange data with third-party vendors to help augment internal datasets.
   • Break down data silos by scaling multiple data sets from different sources within your organization.
   • Find and consume data on other Data Exchanges to get business insights.
3. Speed of Processing
   • Snowflake’s multi-cluster shared data architecture is designed to process enormous quantities of data with maximum speed and efficiency.
   • All data processing horsepower within Snowflake is performed by one or more clusters of computing resources.
   • Data is cached locally within computing resources, along with the caching of query results, to improve the performance of future queries.
4. Cost Benefits
   • The costs for sharing data with Snowflake are minimal and straightforward.
   • Simply pay for the data you store, i.e., you only pay for what you use.
   • Reduce extract, transform, load (ETL), and data pipeline maintenance costs.
5. Control and Govern Access
   • Managing membership
   • Granting and revoking access to data through standard and personalized listings
   • Auditing data usage
   • Applying security controls to your data

Snowflake promises to accelerate the data exchanges by reducing the barriers to access data and time to market. It increases the intrinsic value of data by allowing to share and access of data between providers and consumers.

Real-life Implementation

A famous telecom organization in Europe was sitting on large silos of data that they could not monetize properly because of the complex architecture of the data warehouse operations and data security challenges involved in the data sharing process. The company has Customer Daily Records (CDR) of its subscribers that contains location data of the users. This data can be used to identify the places people visit and help with building consumer profiles. The gathered data allows advertisers to target messages to specific users while tracking whether they visited a retail store after seeing a mobile ad. This helps them plan personalized marketing strategies and business goals based on demography profiles for targeted users. However, due to the data privacy policies of the European Union like GDPR, organizations were struggling to share data with their potential clients. The GDPR policy makes it mandatory for organizations to ensure that the customer's personal information is not shared with third parties without the customer's consent and involves hefty fines and penalties for the data breach. Even the data sharing process was a source of concern as the data was often shared in text/excel files because of the different database architecture of the clients. With growing data privacy concerns and challenges in creating datasets adhering to the GDPR policies, organizations are strictly asked not to share customer data with third parties. The current system architecture forced the organizations to employ a large number of resources to extract the data from the database system and ensure that customer data is not compromised at any point. The companies were evaluating the possibilities of a potential system that would help them monetize the data they currently hold. The introduction of Snowflake into the organizational architecture solved the data monetization problem and improved the overall data culture in the organization. The unique architecture of Snowflake separates the data storage and computation layer to enhance organizational productivity. The pay as you use policy of the Snowflake and the zero maintenance of infrastructure helped the organization phase out the complex on-premise solutions required to handle the huge data volume. Easy connectivity with the existing solutions used for data analytics practice and on the fly scalability of the computation layer helped the organization increase productivity. It also paves the way for seamless integration to the organization's architecture. The Data Marketplace of Snowflake ensured secure data sharing with third parties adhering to the GDPR policies. The in-built data security policies and features minimize the role of organizations to provide data privacy as well. This enables the organizations to make only those data points visible to end-users that they seemed apt for sharing. It also ensures that the data always resides in the organizational Snowflake database rather than on third-party databases. Moreover, the organizations could reach out to thousands of potential clients through Snowflake Data Marketplace without relying on any intermediatory sources. All this ultimately brings out the scope of using the existing data to drive revenue to the organization and highlights the importance of having a complete environment like Snowflake to capture, preserve, access, and transform data. Authors: Rahul Vijayan, Firdous Maqbool

Tableau Cloud Manager

Tableau Cloud Manager is an enhancement to Tableau Cloud that allows customers to create and manage multiple Tableau sites with centralized management of licenses and users. Tableau Cloud Manager simplifies the expansion and administration of your cloud analytics environment, helps ensure you meet governance and data residency requirements and introduces new administrative efficiencies. The highlights of Tableau Cloud Manager are: 1. Expand analytics across your organization with multiple Tableau Cloud sites Tableau Cloud Manager enables Tableau Cloud customers to create and manage multiple sites in a single deployment. Additionally, Tableau Cloud Admins can deploy these sites in the regions of their choice. This functionality is particularly beneficial for global organizations with geographically dispersed teams. By allowing for the establishment of region-specific sites, Tableau Cloud Manager enables tailored analytics experiences that cater to the unique needs and compliance requirements of every team in your organization. Your Tableau Cloud edition determines site limits: • Tableau Cloud (standard): up to 3 sites • Tableau Cloud Enterprise: up to 10 sites • Tableau+: up to 50 sites 2. Effectively manage multi-site deployments Tableau Cloud Manager acts as a layer atop your Tableau Cloud sites, offering centralized management features that help you scale your analytics operations. Customers who deploy multiple sites can manage sites and license users in one place, including granting users access to multiple sites without requiring distinct licenses for each site. 3. Enhance governance with a new Cloud Admin role Tableau Cloud Manager also introduces a new Cloud Admin role, a level above the traditional Site Admin. This allows for more flexibility in how your organization manages and governs your analytics environment based on your unique needs. A smaller organization may employ the same person as a Cloud Admin and a Site Admin. For larger organizations, your Cloud Admin could be someone in IT using higher-level administrative capabilities to implement more control and coordination across your Tableau Cloud sites.

Multiple External Identity Providers on a Site

You can now enable up to 20 identity providers on a single Tableau Cloud site. This feature allows administrators to offer secure access to external users, internal users, and partners. By using multiple identity providers, you can achieve site consolidation and simplify access for both internal and external users throughout the organization.

Table Viz Extension

Transform traditional reporting into visual analytics while addressing your users' needs. Tables are essential visualizations for analysts, allowing them to examine data as text and convey detailed information at a granular level. The Table Viz Extension, developed and maintained by Tableau, enables you to incorporate detailed tables and grid views into your dashboards for users who favor traditional reporting formats. You can load this new visualization type into your marks card, configure new columns by dragging fields onto the card, and interact with the table directly for customization.

Spatial Parameters

Tableau 2024.3 introduces the full Tableau experience for geospatial data with the support of Spatial Parameters. In addition to the standard parameter types (such as string and integer), authors can now choose a “Spatial” type. These parameters create rich, interactive dashboards that allow you to ask and answer questions about geospatial information. The Spatial type enables the parameter to capture spatial geometries—points, lines, and polygons representing locations, paths, and regions. With Spatial Parameters, end users can select individual points, which are then passed as input into calculations, facilitating dynamic behavior based on their selections. This functionality is similar to existing parameter behavior but is now extended to include spatial objects. Read more about spatial parameters: https://beinex.com/topics/spatial-parameters-enhancing-geospatial-analysis-and-adding-interactivity-to-your-maps/

Display Data Model for Published Data Sources

Gain a visual understanding of how tables within your data model are related to Published Data Sources. You can view the relationships between tables and fields in Tableau by simply clicking on the Data Source pane in a Tableau workbook. By enabling analysts to see and comprehend how tables in the data model are interconnected in Published Data Sources, they can confidently create accurate visualizations with a clear understanding of the data model's semantics.

Tableau Cloud App for Microsoft Teams

The new Tableau Cloud App for Microsoft Teams allows users to seamlessly integrate data-driven insights into their daily workflows, resulting in faster and more efficient decision-making. This integration enables real-time data sharing, making it easy for users to share their favorite Tableau dashboards and Pulse metrics without leaving Teams—in personal apps, messages, channels, and meetings. From there, they can analyze and share their insights in a message or channel. Pinned channel content is also available to explore in Teams meetings, providing a fully interactive experience. This promotes a more data-driven culture by ensuring everyone can collaborate effectively with access to the same data and analytics. Image source: https://www.tableau.com/products/new-features

How Beinex Can Assist You

Beinex, a premier Tableau partner, offers sustainable analytics solutions to organizations and enhances their internal data visualization capabilities through customized training programs. Our team of Tableau-certified consultants consists of experienced Tableau business users who are passionate about the platform and committed to delivering an exceptional experience. Connect with us to embrace transformation: https://www.beinex.com/free-tableau-software/

What is Business Intelligence?

Business intelligence (BI) is an analysis that uses business-related strategies and technologies to assess, process, and interpret business information. This type of information helps businesses understand the current state of their organization and make informed decisions on how to take actions that are likely to yield their intended results.
Leveraging business intelligence insights offers several benefits to employers and employees, including strengthening performance and improving efficiency. For example, insights from business intelligence metrics can help employers understand where supply chain function might be breaking down or provide a snapshot of consumer products performing above or below expectations.

Top Trends in Business Intelligence in 2024

Finding the latest trends in BI can help your organization stay competitive and maximize your ability to use your data. While trends continually shift by nature, the following areas have rapidly risen in demand and application.   

1. Augmented Analytics

Augmented analytics is an approach to data analytics that employs advanced technologies such as AI and machine learning to automate data preparation, insight generation, and insight sharing.
In 2023, the global augmented analytics market was valued at USD 8.9 billion, marking a significant milestone in data-driven technologies. The market is on track for impressive expansion, with estimates predicting its value will climb to USD 11.6 billion in 2024 and soar to USD 91.4 billion by 2032. This remarkable growth, reflected in a compound annual growth rate (CAGR) of 29.4% between 2024 and 2032, underscores the rising importance of advanced analytics in transforming business intelligence and decision-making processes across industries.
Here are the advantages of augmented analytics:
Advantages: • Increased Efficiency: Automates data preparation, saving up to 60% of man-hours spent on manual data processing. • Broader Accessibility: Empowers non-technical users to gain insights, reducing dependency on data specialists by 40%. • Real-World Impact: Organizations using augmented analytics report a 25% increase in productivity due to faster decision-making.

2. Natural Language Processing (NLP)

Natural Language Processing (NLP) is a confluence of computational linguistics and artificial intelligence that enables machines to understand, interpret, generate, and respond to human language meaningfully and contextually. An example of a program that utilizes natural language processing is ChatGPT. The Natural Language Processing (NLP) market is projected to reach a value of USD 36.4 billion in 2024. With a robust compound annual growth rate (CAGR) of 27.5% from 2024 to 2030, the market is expected to expand significantly, reaching a volume of USD 156.8 billion by 2030. This rapid growth highlights the increasing adoption of NLP technologies across various industries, driving advancements in AI-driven communication and analytics tools. The advantages of Natural Language Processing (NLP) within the business intelligence landscape: Advantages: • Enhanced User Engagement: Reduces the learning curve for data tools, increasing user adoption by up to 30%. • Customer Insights: Companies using NLP for sentiment analysis report a 15% increase in customer satisfaction.

3. Data Storytelling

The growing dependence on data in the corporate landscape brings forth the need for data interpretation that extends beyond traditional methods. The narrative structure is one of the primary differentiators between data storytelling and data visualization. While data visualization can provide a visual representation of what the data is saying, data storytelling explains why the data matters, providing a more comprehensive understanding of the insights. According to Gartner, by 2025, data stories will become the most common method for consuming analytics, and data storytelling will dominate BI, with 75% of these stories being automatically produced through augmented analytics techniques. Advantages: • Better Understanding: Enhances comprehension of complex data, leading to a 20% reduction in misinterpretation. • Improved Decision-Making: Organizations using data storytelling have reported a 15% increase in strategic decision outcomes.

4. Self-Service Analytics

Another BI trend is self-service analytics. It is a form of business intelligence wherein end-users, such as marketing professionals, are enabled to conduct data analyses and generate reports without the direct assistance of IT or data science teams. The self-service BI market is projected to reach USD 30 billion by 2036, expanding at a compound annual growth rate (CAGR) of 8% between 2024 and 2036. In 2023, the market size was valued at over USD 18 billion. This substantial growth is driven by the increasing demand for data democratization, as organizations seek to dismantle traditional data silos and enable non-technical users to access, analyze, and extract insights from data independently. Advantages: • Time Savings: Reduces report generation time by up to 50%, allowing for faster data-driven decisions. • Empowered Employees: Decreases IT workload by 30%, enabling more focus on strategic projects.

5. Decision Intelligence

DI goes beyond traditional analytics by creating a semantic framework that incorporates business rules and context, enabling predictive analytics to generate actionable, future-focused insights. This empowers organizations to make more informed and strategic decisions, often automating routine choices and accelerating complex ones. The DI market is on a robust growth trajectory, projected to surge from $13.3 billion in 2024 to a remarkable $50.1 billion by 2030. As businesses increasingly prioritize data-driven strategies, DI stands out as a pivotal tool for enhancing decision-making agility and precision, ensuring organizations stay ahead in a competitive landscape. Advantages: • Automated Decision-Making: Increases decision speed by up to 40%, significantly reducing time-to-insight. • Enhanced Strategic Planning: Companies using DI report a 25% improvement in strategic planning accuracy.

6. Predictive Analytics

Predictive analytics is an advanced form of analytics that uses historical data, statistical algorithms, and machine-learning techniques to predict future events and trends. The predictive analytics market is projected to grow by USD 38.6 billion, at a CAGR of 28.9%, between 2023 and 2028. This rapid expansion is fueled by increasing demand for data-driven decision-making, advancements in AI and machine learning technologies, and the rising adoption of predictive analytics across various sectors, including finance, healthcare, and retail. Advantages: • Proactive Decision-Making: Reduces operational costs by up to 15% through accurate demand forecasting. • Risk Mitigation: Enhances risk assessment accuracy, leading to a 20% reduction in potential losses.

7. Artificial Intelligence (AI) in BI

Another emerging BI trend is the greater infusion of AI in business intelligence. AI's ability to automate data analysis, generate insights, and predict outcomes is redefining the way organizations interact with data. The Artificial Intelligence market is projected to reach a size of USD 184.0 billion in 2024, with an expected annual growth rate (CAGR) of 28.4% from 2024 to 2030. This growth is anticipated to result in a market volume of USD 826.7 billion by 2030. AI in BI typically involves the application of machine learning algorithms and advanced analytics techniques to automate data processing and interpretation tasks. From data collection and cleaning to analysis and insight generation, AI can significantly reduce the manual workload, speeding up the entire BI process. Advantages: • Operational Efficiency: Automates 70% of data analysis tasks, freeing up resources for strategic activities. • Cost Reduction: Reduces the cost of data processing by up to 20%

8. Advanced Data Visualization

Advanced data visualization goes beyond basic charts and graphs, incorporating a variety of innovative visual elements such as heat maps, geographical maps, scatter plots, treemaps, and more into the dashboard design. These elements enable the presentation of multi-dimensional data in a single view, facilitating a more comprehensive understanding of the data. The global data visualization market showcased a strong value of USD 4.5 billion in 2017, highlighting the growing demand for effectively presenting complex data. By 2023, the market is expected to surge to USD 7.7 billion, reflecting a robust CAGR of 9.47%. Advantages: • Improved Insights: Increases data interpretation accuracy by 30%. • Enhanced Collaboration: Boosts cross-departmental collaboration by 25% through shared visual insights.

9. Mobile BI

Mobile business intelligence (BI) involves the use of mobile devices to access BI applications and data, enabling decision-makers to stay informed and make decisions, irrespective of their location. The global mobile business intelligence market, valued at USD 13.8 billion in 2023, is expected to grow at a CAGR of 15.3%, reaching USD 51.5 billion by 2032. Advantages: • Increased Accessibility: Provides real-time data access, enhancing decision-making speed by 35%. • Boosted Productivity: Enables on-the-go analysis, increasing productivity by 20%.

10. Ethical Data Governance

The last BI trend on the list is ethical data governance, which addresses policies, procedures, and structures that ensure data quality and security, and ethical considerations related to data collection, processing, and use. The global data governance market is projected to reach USD 4.1 billion in 2024 and is expected to grow at a CAGR of 18.5% over the next decade, reaching USD 22.5 billion by 2034. The central principle behind Ethical Data Governance is respecting individual privacy and rights in all data activities. It involves implementing practices that ensure informed consent, data anonymization, and stringent access controls, among others, to protect individual privacy and prevent data misuse. Advantages: • Compliance Efficiency: Reduces compliance-related costs by up to 25%. • Increased Trust: Builds customer trust, leading to a 10% increase in brand loyalty.

Tableau in Action: Leveraging Latest BI Trends

Tableau integrates the latest BI trends into practical applications, enhancing decision-making and data insights. Let’s examine how some of the top BI trends are applied within Tableau. Here are a few examples:

1. Augmented Analytics: With Tableau Einstein Discovery, companies can automate insights and speed up decision-making, especially in retail and finance.
2. Natural Language Processing: Tableau’s NLP system allows users to explore data using simple language, enabling faster data processing without coding.
3. Data Storytelling: Story Points help craft compelling narratives, increasing stakeholder engagement in areas like marketing and sales.
4. Self-Service Analytics: Tableau enables business users to independently explore data, reducing IT workload and accelerating decisions in finance and supply chain.
5. Predictive Analytics: Integrating with Einstein Discovery, Tableau’s predictive capabilities help industries like healthcare forecast trends and optimize operations.
6. Mobile BI: Tableau’s mobile app allows for real-time access to data, improving productivity for on-the-go teams like sales.

For a free Tableau demo, connect with us: www.beinex.com/free-tableau-software/