How are Data, AI and Automation transforming the Business?

Let's explore how Data, AI, and Automation are transforming businesses by discussing some tracks from the IBM Data, AI and Automation Forum - Canberra that address common business challenges and how IBM solutions can help address them.

Attending the IBM Data, AI and Automation Forum - Canberra is a valuable investment of your time due to the high-quality education, actionable insights, and networking opportunities provided. With over 30 experts and user practitioners offering 25 sessions, attendees will gain extensive knowledge and practical skills. This forum is designed to help data and AI professionals gain valuable insights into the most cutting-edge tools and methodologies in the industry. The forum will cover various tracks, including data management, analytics, strategy, and value, data science, machine learning, artificial intelligence, trust, governance, privacy, and technical insights for data and analytics practitioners. These tracks will highlight current and future data management strategies, analytics capabilities, and their impact on business outcomes, developing a coordinated strategy and operating model, talent development and skill requirements for successful deployment of data science, ML, and AI, as well as governance practises for trusted, agile data and analytics, and AI.

Make a note of Wednesday, May 24, 2023, 8:30 a.m. - 5:00 p.m. AEST, and Register now!

By the end of this article, readers will have a better understanding of how Data, AI, and Automation can be leveraged to drive business success.

In today's data-driven world, the importance of data cannot be overstated. However, various organisations are struggling with challenges in handling their data.

A recent Seagate Technology report reveals that 68% of enterprise data is not analysed, while a Corinium study shows that 80% of time spent on data management is dedicated to cleaning, integration, and preparation. Another Corinium report highlights that 82% of organisations consider data quality a significant barrier to their data integration projects.

These proof points demonstrate the depth and complexity of the challenges that organisations are facing in utilising their data effectively.

Data-driven innovation is no longer limited to business analysts and data scientists; every employee now needs access to consumable data to gain useful insights. Employees across departments want to use data and AI to optimise various aspects of their roles, from marketing to finance to IT. However, data is often still siloed within organisations, and there is a need for a better way to manage it so that everyone has equal access. A new emerging technology called "data fabric" can help address this issue.

Many employees struggle to access the data needed to make informed decisions, and even if they can access it, they may find it difficult to extract insights from it. Organisations need to address these problems to ensure that every employee can confidently work with data to make the right decisions for their roles.

👉The challenge lies in creating a future-ready enterprise that is built on plans, spreadsheets, and ad-hoc reports for analysis, as well as outdated systems that are not linked with other parts of the business. Employees are frustrated with the time it takes to make decisions, and the systems and processes they must work with are often unable to keep up with the pace of decision-making that is required.

To support the primary objective of making the best strategic decisions to increase profitable revenue growth, organisations must overcome data and planning silos and encourage collaboration, link strategic decisions to successful execution, eliminate the risk of inaccurate insights, develop more accurate plans and forecasts with agility, and continuously update plans, forecasts, and budgets in real-time.

As organisations face these challenges and embrace solutions to overcome them, they must ensure that every employee has equal access to data and can confidently work with it to make the right decisions for their roles. The Tack below explains how Continuous and Accurate Planning with IBM Planning Analytics with Watson.

As companies strive for success and resilience, there is a growing focus on new data applications. According to Gartner , Extended Planning and Analysis (xP&A) is an emerging trend that promises to streamline and integrate planning across every part of an organization. IBM #PlanningAnalytics with #Watson is leading the way in xP&A with its AI-powered #planning solution. In this session, you will learn how it automates and simplifies planning processes to enable greater accuracy and continuous planning.

👉We all know, that Data is generated at an unprecedented rate, and with the ease of creating databases, the number of data sources is increasing rapidly. This poses several challenges for businesses, especially regarding data sovereignty and compliance with regulations. 

As the volume of data increases, businesses need to handle an ever-growing number of use cases, including regulatory compliance, operational analytics, business intelligence, data science, and more. However, with this comes a higher risk of compliance, security, and governance issues, leading to more complexity and requiring a higher level of effort to enforce policies and perform data stewardship. 

Managing multiple data platforms and tools also results in higher costs and more reliance on IT. This means less self-service for business users and slower collaboration, ultimately leading to a slower time-to-value. To overcome these challenges, businesses need a comprehensive data strategy that enables data democratisation and efficient collaboration while ensuring data security, compliance, and governance. The Tack listed below explains, How ,Why Your Data in Motion Needs Your Attention

#Dataobservability is a critical component of any modern data system, allowing you to monitor the health and state of data both in motion and at rest. This encompasses a wide range of activities and technologies, from real-time issue identification and troubleshooting to proactive resolution of potential problems. In this session, we'll explore why IBM believes that data observability is essential for customers, and how we can help you achieve it. Don't let a critical data pipeline failure or unexpected null record derail your operations – learn how to keep your data moving smoothly and efficiently. A clear data quality strategy is essential for proactive data quality management as data moves from producers to consumers. Gartner has recognised "data fabric" as a core architecture for data-driven teams, and #IBM has been leading the space within that. Recently, Gartner created a new category around data observability, which is catching on within the #DataQuality, Management and #datafabric space. Data observability is the foundation for reliable data as it provides mechanisms to observe changes in data, data pipelines, data infrastructure, and user behaviour. With the increasing complexity of data stacks, observability has emerged as a critical concern for data teams. Unreliable data is the most expensive problem that enterprise data teams face today; it's not enough just to have data, enterprises need to learn how to trust it and know how to use it too. Databand.ai is IBM's data observability solution that helps detect #dataincidents earlier and resolve them faster. It offers central alerting, custom alerts, and pipeline monitoring capabilities that help users hit all five steps in proactive data observability, delivering reliable and trustworthy data.

👉Achieving a single view of the customer is critical for organisations looking to drive revenue, improve customer experiences, and comply with data privacy regulations. However having data spread out across multiple silos can lead to inconsistencies, data quality issues, and an incomplete view of the customer. The Tack listed below explains how to Obtain a single view of the customer with ease using IBM Match 360.

IBM Match 360 works by first ingesting customer data from multiple sources, such as CRM systems, marketing automation platforms, and social media channels. The solution then uses machine learning algorithms to match and merge customer data based on predefined rules and criteria.

👉Real-time data processing has become increasingly important for businesses in today's fast-paced world. However, traditional data architectures often create obstacles in achieving this goal, especially for those relying on single-node legacy databases. The Tack listed below explains how to Unleash the power of your data with real-time applications & analytics.

During this session, you'll learn how #IBM and #SingleStore can help you create the ultimate foundation for real-time data processing. You'll discover how to leverage SingleStore's in-memory technology and distributed architecture, coupled with IBM's expertise in technology and innovation, to deliver fast access to data, scalability, reliability, and real-time analytics. With IBM and SingleStore, you'll be able to achieve true real-time data processing. Real-time means immediate and accurate, and with this partnership, you can deliver real-time experiences to your customers every time. Don't let traditional data architectures hinder your organisation's growth and success

👉#ArtificialIntelligence (#AI) has the potential to transform businesses and improve our lives, but this transformation cannot happen if people do not trust AI. This is why building trust and security into AI and automated decision making is crucial. The adoption of AI is on the rise, but the deployment of these algorithms is facing challenges such as disparate datasets, siloed teams duplicating efforts, and concerns about the privacy and security of data. In order to overcome these challenges, companies need to take a multifaceted approach to build trusted AI solutions. The Tack listed below explains The importance of trusted AI and Building trust and security into AI and Automated Decision making

IBM is at the forefront of developing cutting-edge AI technology that is transparent, explainable, and respects people's data and insights. IBM has a strong commitment to building trust in its AI solutions, which is why many companies around the world are leveraging IBM's technology to build trusted AI solutions.

Building trust into AI starts with data. Organisations need to ensure that they have accurate and relevant data that is free of bias. This can be achieved by using tools that help identify and mitigate bias in the data. IBM's #Watson #OpenScale is an example of such a tool. It allows organizations to track and explain how AI models make decisions, detect and mitigate bias, and monitor for drift in model performance over time.

Another way to build trust into AI is through transparency and explainability. AI models must be able to explain how they arrived at a particular decision. This helps build trust by providing insights into how the AI model works and how it arrived at its decision. IBM's #WatsonStudio and #AutoAI are examples of tools that help build transparent and explainable AI models.

In conclusion, building trust and security into AI and automated decision making is crucial for its adoption and success. Companies that take a multifaceted approach to building trusted AI solutions will be well positioned to leverage the full potential of AI and transform their businesses.

Without giving away too much from the forum, I am certain you see from the above the opportunity to gain knowledge and stay up-to-date with the latest advancements in data, AI, and automation.

Summarising the IBM Data, AI and Automation Forum - Canberra offers a unique opportunity for attendees to connect with IBM experts, senior leaders, and like-minded peers from similar organisations. The event provides a platform to exchange ideas and experiences and to broaden perspectives on solving problems related to Data, AI and Automation. By engaging with peers, attendees can discover new approaches, best practices, and opportunities to collaborate. In addition to the knowledge-sharing sessions, the event includes welcome receptions and special evening events in diverse settings, offering a chance to have fun and build new business relationships with peers. 

I am eagerly looking forward to welcoming you to the event, and I am confident that you will gain valuable insights and forge meaningful connections.

👉Make a note of Wednesday, May 24, 2023, 8:30 a.m. - 5:00 p.m. AEST, and Register now!

Please feel free to contact me for further information or  Nicholas Renotte , Trevor Noseda , Michael Lim , Ross Farrelly, PhD , Deon George , Natalie Gunn , Kevin Jessop , Stephen Du , How Ming Yong , Kristian Smythe , Mary-Jane Goddard , Ian Godsell , Stuart Maclean , Gavin Fernandes , Billy Apoleska , Matthew Plint , Adam Makarucha

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