{"id":8577,"date":"2024-12-04T01:00:00","date_gmt":"2024-12-04T01:00:00","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=8577"},"modified":"2024-11-29T09:47:05","modified_gmt":"2024-11-29T09:47:05","slug":"what-is-data-transformation","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/ap\/blog\/what-is-data-transformation\/","title":{"rendered":"What is Data Transformation and How Can it Help ASEAN Unlock AI\u2019s Potential?"},"content":{"rendered":"\n

AI has the power to revolutionise your business \u2013 but only if your data is ready. Discover how business leaders in ASEAN are turning disconnected data into actionable insights, and why data transformation is essential for unlocking AI\u2019s full potential.<\/h2>\n\n\n\n

Before AI can deliver on its promised value, organisations must first examine their data. Simply collecting large volumes of information isn\u2019t enough \u2014 data must be accurate, well-organised, and ready for analysis. Raw data often requires transformation into clean and enriched formats so AI can generate actionable insights and deliver personalised experiences that create tangible business value. <\/p>\n\n\n\n

With 32% of organisations in Singapore already using AI<\/a> across a range of use cases, and 66% planning to implement it within the next 6-18 months, getting your data in AI-shape has never been more critical. <\/p>\n\n\n\n

Is your data ready to meet the challenges of AI, or is your business at risk of falling behind? <\/p>\n\n\n\n

What is data transformation and why does it matter for ASEAN?<\/h2>\n\n\n\n

Data transformation involves converting, structuring, and unifying data so it can be effectively used by a system. It\u2019s essential for businesses that want to take the vast amounts of data they have access to and activate it to improve customer experiences, make smarter decisions, and increase operational efficiency. <\/p>\n\n\n\n

Businesses across ASEAN collect data from a variety of sources, including digital channels, customer support, and connected devices. However, this data is often fragmented across different systems, with the same customer appearing under different profiles in each, making it hard to see them as a single entity. This lack of cohesion means businesses can miss key insights and lose potential value. <\/p>\n\n\n\n

Overcoming disjointed data and building a unified customer profile is essential to realising the potential of AI across sales, service, marketing, and commerce \u2014 not only to increase efficiency in the back-office but also to unlock new value in customer-facing, front-office functions.<\/p>\n\n\n\n

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As Alvin Neo,  Chief Customer and Marketing Officer, FairPrice Group and Managing Director, NTUC Link explains in Unlocking Opportunity in the Data and AI Revolution<\/a>: \u201cFundamentally, the foundation of AI is data, that is why a major priority for us is ensuring that our data is clean and well organised. This is because the full value of AI is achieved when you can use it at scale, and we can only safely use it at scale if we have that data foundation in place.\u201d<\/p>\n\n\n\n

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Unlock the Power of Data for AI<\/h2>\n\t\t\t\t\t\t\t

See how ASEAN businesses are readying their data for the future of AI.\u00a0<\/p>\n\t\t\t\n\t\t\t\n\t\t\t\t\t\t\t

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Data transformation offers a competitive edge for ASEAN<\/h2>\n\n\n\n

In an AI-driven world, data transformation is not just a technical task but a strategic imperative for businesses across ASEAN. In Singapore, 89% of businesses<\/a> believe that AI will be somewhat or very critical across a range of use cases, including developing hyper-personalisation and identifying new sales opportunities. And having accurate and secure data is the foundation of AI success. <\/p>\n\n\n\n

As Minh (Martin) Tran, Global Sales Development Manager at FPT Software shares: \u201cIntegrating Einstein has streamlined our operations with predictive analytics. We can target the most promising prospect by combining AI with human expertise.\u201d<\/p>\n\n\n\n

Simply put, AI makes it possible for businesses to streamline processes, empowering teams to solve problems faster and deliver better customer experiences. <\/p>\n\n\n\n

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Understanding types of data transformation<\/h2>\n\n\n\n

Data transformation can be broken down into several processes that ensure data is clean, structured, and ready for AI-powered systems. These processes are generally grouped into four key classifications: <\/p>\n\n\n\n

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  1. Data cleaning and preprocessing: <\/strong>This includes tasks such as imputation, outlier detection, data standardisation, and normalisation. Cleaning ensures that AI models work with accurate, high-quality data.<\/li>\n\n\n\n
  2. Data aggregation and summarisation: <\/strong>Data is grouped and summarised to enable analysis at higher levels, improving the clarity of insights generated by AI tools. Techniques like rolling up and pivot tables are common here.<\/li>\n\n\n\n
  3. Data derivation and enrichment:<\/strong> New data can be derived through feature engineering, while enrichment involves adding context to existing data, making AI more effective in delivering insights.<\/li>\n\n\n\n
  4. Data integration and transformation: <\/strong>Unifying data from different sources (merging, joining) and ensuring it flows correctly into AI systems is critical for maintaining data consistency and accuracy.<\/li>\n<\/ol>\n\n\n\n

    What tools can organisations use to implement data transformation?<\/h2>\n\n\n\n

    Once you understand the \u2018what\u2019 and \u2018why\u2019 of data transformation, the next step is \u2018how\u2019. <\/p>\n\n\n\n

    In Singapore, 96% of business leaders <\/a>agree that a strong data strategy is crucial, yet only 30% report having one integrated across their business. <\/p>\n\n\n\n

    Bridging this gap in data readiness is critical to unlocking the power of AI \u2014 and the right tools make it simpler and easier to do so.<\/p>\n\n\n\n

    As the only data platform native to the #1 AI CRM, Salesforce\u2019s Data Cloud <\/a>allows ASEAN businesses to unify data without moving or duplicating it, thanks to its zero-copy architecture. With over 200 out-of-the-box connectors, Data Cloud simplifies the process of activating data in real-time \u2014 minimising complexity, reducing costs, and lowering both security and data cleanliness risks. This provides businesses with a comprehensive, up-to-date 360-degree view of each customer.<\/p>\n\n\n\n

    MuleSoft<\/a> complements Data Cloud by seamlessly connecting systems and integrating data across departments, unlocking even more value from existing data and extending Data Cloud\u2019s capabilities. Together, they empower businesses to derive actionable insights and deliver personalised customer experiences efficiently.<\/p>\n\n\n\n

    With Mulesoft and Salesforce\u2019s Data Cloud for Marketing<\/a>, Lotus\u2019s<\/a> \u2014 a major retailer in Thailand and Malaysia \u2014 was able to unify its data, eliminating duplicate records and halving the overall volume. This not only streamlined the data but also enriched the remaining records, making them more valuable for activation. As a result, Lotus\u2019s gained a comprehensive view of its 9 million customers that could be activated directly in the flow of work.  <\/p>\n\n\n\n

    Tools like Agentforce<\/a> and Prompt Builder<\/a> make it possible to automate tasks, personalise workflows, and surface insights, unlocking new opportunities for informed decision-making and operational efficiency. The key to unlocking trusted, relevant responses from AI lies in unified data. By integrating data across departments, AI agents deliver accurate recommendations, efficiently route cases to representatives when necessary, and ensure faster resolutions \u2014 enhancing customer satisfaction while allowing service teams to focus on higher-value tasks. <\/p>\n\n\n\n

    For example, Lion Parcel<\/a> unified customer data from Sales Cloud<\/a> and Service Cloud<\/a> with external sources including warehouse data, to create an integrated view of operations and customer interactions. By segmenting its customer database, Lion Parcel can identify issues based on customer tier and automatically route cases to specialised agents. This approach has led to a 73% reduction in case resolution times. Additionally, by integrating generative AI with Salesforce, AI-powered chatbots now answer 90% of WhatsApp queries, significantly reducing service times and allowing service representatives to focus on more complex tasks.<\/p>\n\n\n\n

    Data security is a top priority in data transformation<\/h2>\n\n\n\n

    As AI becomes integral to business operations, the need for strong data security becomes even more pressing. Businesses are increasingly focused on security, governance, and ethics as they explore new AI use cases and prepare for future advancements.<\/p>\n\n\n\n

    72% of business leaders in Singapore<\/a> cite privacy and security concerns as a barrier to purchasing AI, while 92% agree that trust is critical when partnering with an AI vendor. This highlights the growing need for solutions that not only deliver powerful AI capabilities but also prioritise data protection.

    The     Einstein Trust Layer<\/a> provides a robust set of features and guardrails that protect the privacy and security of your data while improving the safety and accuracy of AI results. Key safeguards include Secure Data Retrieval, which securely grounds AI prompts in business data, maintaining permissions and access controls, and Data Mask, which prevents sensitive information from being exposed or used for training AI models. This means businesses can use AI to ground results in real-time data while keeping that data secure. These protections build confidence in AI by addressing concerns over privacy, security, and ethics \u2014 critical for fostering trust in AI solutions.<\/p>\n\n\n\n

    Towards a data-driven future<\/h2>\n\n\n\n

    To ensure successful and secure AI adoption, businesses must consider the following:<\/p>\n\n\n\n