Big data was supposed to revolutionize things but fell short of its big promises. Now, with AI and new data platforms designed for the AI age, we might just crack the code and finally get the value out of all that data.
Back in 1914, Willard Brinton, an engineer and pioneer in data visualization, noted that despite companies’ efforts to analyze and organize their data, they often needed help to derive valuable insights. He observed that known facts could have been more effectively presented for practical use. This challenge of making sense of and deriving value from what is now termed big data has persisted for over a century.
Today, advancements in artificial intelligence (AI) and data platforms designed for the AI era offer a promising solution to unlocking the value of big data. Rather than revolutionizing how data is processed and stored, the focus is reimagining how it is accessed and distributed within an organization.
One example of this innovative approach is the Salesforce Data Cloud, which integrates all types of big data, regardless of its source. It ensures its accessibility and usability for all business users within their everyday applications. This means that relevant and trusted data is readily available and actionable. Moreover, this data is automatically fed into AI models, providing them with the necessary context to generate high-quality insights.
This integration and accessibility mark a significant departure from previous methods. Finally, all data is unified, harmonized, and accessible across various business applications and user interfaces, representing a substantial advancement of earlier practices.
How Did Organizations Get Here?
In the 1990s, when “big data” became a buzzword, there was this optimism that organizations could leverage this vast amount of data to gain valuable insights about customers and markets, offer incredibly personalized experiences, predict demand with precision, and improve product development, among other benefits. Big data expanded rapidly and became cumbersome, giving rise to an entire industry dedicated to helping companies manage and analyze it. Major challenges persist despite significant investment from enterprise customers in big data solutions like data lakes and data warehouses.
One of the main issues is that data lakes and data warehouses are tailored for technical users familiar with SQL, a computer language used for database manipulation, and semi-structured data such as emails and web pages. As a result, salespeople need help leveraging them to advance deals, service representatives find it challenging to resolve customer issues, and retailers need help creating personalized product promotions.
In essence, these expansive repositories end up confining a company’s data within progressively intricate silos, rendering it inaccessible for practical use across various departments and functions.
A Solution for Big Data
Data platforms like Salesforce Data Cloud and AI assistants like Einstein Copilot tackle this issue head-on. They bridge the gap between your scattered internal and external data sources, providing different sections of your business with a comprehensive understanding of customer behavior and data. But they don’t stop there. These cutting-edge AI-driven data platforms seamlessly integrate information from your data lake or warehouse and link it directly to practical AI tools, enriching everyday processes within your business applications.
Salesforce Data Cloud is the foundation for Einstein Copilot, our innovative generative AI conversational assistant, and Einstein Copilot Builder, a user-friendly tool for crafting and customizing AI assistants. Together, they usher in a new era of AI-powered applications. Thanks to Data Cloud, we can construct a dynamic data graph that offers an up-to-the-minute, unified perspective on customers or any other entity. Plus, users can effortlessly transmit all pertinent data to the prompt with a simple click, which fuels the large language model (LLM). There is no longer a need for cumbersome SQL queries or manual data joins.
The Role of Salesforce, AI, & AI Copilots
AI copilots offer another avenue to utilize the potential of big data. They’re designed for simplicity and seamlessly integrated into your everyday business applications. Just ask it to identify the top three sales leads of the week and explain why they stand out — and it delivers. How does it work? In the background, the copilot leverages Large Language Models (LLMs) to sift through vast volumes of data on your behalf.
This level of capability is achievable when your AI copilot has access to all the data across your organization. While many companies grapple with disparate types of data scattered across various departments and systems, those that can consolidate this data into a unified system stand to fully capitalize on the potential of AI copilots and their big data.
The instant responses provided by your copilot are rooted in comprehensive business data sourced from all corners of your organization, not limited to sales, marketing, or customer service systems. Tasks designed for copilots are empowered with access to this extensive business data, including information that was previously challenging to analyze, such as PDFs, web pages, and emails. This broader scope of accessible data enhances the copilot’s ability to deliver accurate and insightful responses across various tasks and scenarios.
Big Data and AI – Like Salt and Pepper
Several factors have fueled the remarkable surge in data volume over the last decade, such as the decreasing storage cost, the widespread adoption of online services, and the Internet of Things (IoT) expansion. This year, the amount of data generated, captured, copied, and consumed is projected to reach a staggering 147 zettabytes (that’s a one followed by 21 zeros), nearly double the levels seen in 2021.
This wealth of data holds valuable information and insights, provided you can effortlessly access, process, and integrate it into your everyday tasks. Fortunately, with the advent of Salesforce’s AI capabilities and data platforms tailored for the AI era, you now have access to such tools. You don’t need to be a data scientist to gather all your enterprise data, you can just hire a trustworthy Salesforce development partner and eliminate all these problems.
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<p>The post Can Salesforce & AI Fix Big Data’s Broken Dreams? first appeared on PureLogics | Technology Services and Solutions.</p>