Natural Language Technologies Augment Data Visualization

In the ongoing effort to derive insights from massive troves of data, businesses are increasingly realizing the benefits of presenting data in a visual format. Indeed, any enterprise BI tool worth its weight will come prebuilt with some degree of data visualization capabilities, allowing analysts to craft a coherent story from raw data.

But many times, simply visualizing data is not enough. Most internal stakeholders who need to grasp the importance of the data are not themselves data visualization experts. One can understand their struggles, when visualizations often necessitate representation of multiple dimensions through size, color, shape and spatial proximity. Our capacity to transform data for visual consumption has improved greatly, but the interpretation of those visuals is often far from effortless. Business users need data to tell them a story, and to do so with the least amount of manual drilling, screen staring and head scratching.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

"One of the ultimate goals for an agile BI environment is end-user successful self-service"

Enter artificial intelligence–which should come as no surprise. Two AI technologies in particular are poised to augment the way we consume data visually by allowing us to have ‘conversations’ with our charts and dashboards. Natural language processing (NLP), by which algorithms parse everyday speech to determine meaning, will let users ask questions in place of conventional querying. Natural language generation (NLG) can then map data to concepts, and render them in a colloquial format for easy consumption. The onset of these capabilities will provide:

Faster Time to Insights

NLP technologies will drastically reduce the number of “clicks to insight” required by users. In lieu of dragging and dropping variables, and manually drilling down, business analysts will simply be able to type a question in plain language and the visualization will adapt accordingly. What’s more, users often waste time sifting through massive data sets to determine what the attribute or variable they’re interested in has even been named. After parsing a user’s question, these tools can map inputs to a catalogue of synonyms, determine semantic meaning, and search for the most relevant variable/attribute to display in the visualization.

Reduced Skill Requirements

One of the ultimate goals for an agile BI environment is end-user successful self-service. But obvious barriers exist, as not everyone in your organization can be expected to have proficiency in an enterprise BI tool, or even in the basics of data visualization. NLP capabilities only require that a business user know what question they want answered with no need to search for the exact tool or control necessary to manipulate the visualization. Auto completion features can offer suggestions while the user is mid-sentence to guide them toward words/phrases most closely linked with the fieldsthat exists in the visualization’s data set. Perhaps most importantly, NLG allows even the least skilled user to glean meaning from a chart or dashboard, diminishing the chance for misinterpretation of data, and leading to better decision-making.

More Natural Interactions

Users often know, in a conversational sense, what they want to get from visualization, but lack the skills to “translate” it into the language of data visualization environment. Much like advanced data visualization capabilities supplanted traditional SQL with visual querying, the conversational query will soon become the norm. “How many apartments were sold in Brooklyn in March 2016?”Imagine that this query updates a map of the NYC metro area to zoom in on Brooklyn and display all apartments sold in the borough during the time frame specified. As these tools develop stronger semantic understanding, users will be able to ask follow-ups exactly like they would in human interactions. “What about in May?” In Tableau’s Eviza prototype, the visualization can “remember” that you’re interested in Brooklyn, specifically sales in 2016, but will update the month to the new desired timeframe.

Deeper Explanations of the Data

On a micro-scale, certain tools allow users to enter queries as simple as “What do the biggest circles represent?” and receive a simple readout explaining the relevance of sizing for that given element. On a larger scale, NLG tools such as Wordsmith (which already has integrations with Tableau, TIBCO Spotfire, MicroStrategy, and even Excel), allow data scientists to create templates whose rules dictate how a given data chart is translated into plain language. Developers can decide exactly which metrics and timeframes matter most, and even customize the language to incorporate lingo specific to an individual business. In effect, this disambiguation of data interpretation means more consistency of insights and decisions across the organization.

More in News

Texas, with its vibrant culture, historical significance, and vast landscapes, is gaining recognition as an emerging leader in the digital sector. Various cities throughout the state are becoming pivotal in the global tech landscape, drawing in startups, entrepreneurs, and major technology firms. This evolution is remarkably reshaping social connections, job opportunities, and community values, underscoring the region's swift progress and increasing attractiveness as a technological hub. Despite having a significant military presence, the city has emerged as a leader in telecommunications and cybersecurity. Texas has cemented itself as a significant player in the global IT sector, with its towns acting as centers for specialized industries like cybersecurity, energy technology, and medical innovation. Cultural changes have resulted from the expansion of the IT industry, especially in the way residents view life and work. Texas’s entrepreneurial spirit and historic principles of self-reliance and tenacity have created a vibrant commercial and innovation climate. The tech industry’s emphasis on work-life balance has further impacted the state’s culture. Many companies provide remote work options and flexible hours, allowing inhabitants to engage in personal interests, explore side projects, and spend more time with family. Educational institutions have increased their technology-focused programs in response to the rapidly expanding tech industry, training students for professions in data science, engineering, and software development. Students from all across the nation and abroad have been drawn to this surge in tech-driven education, which has helped to create a growing, diverse workforce. With coworking spaces, incubators, and events that unite investors and entrepreneurs, the state’s startup environment has also fostered a collaborative culture. This environment encourages creativity, collaboration, and idea sharing, which will help produce the forthcoming crop of tech innovators. Although the internet boom has boosted the economy and created job opportunities, it has also brought along problems, including increased living expenses, traffic, and housing costs. Local governments are now concentrating on sustainable growth methods to solve these problems and guarantee that everyone in the community can profit from the digital industry. As Texas evolves, the tech industry’s impact on the state’s culture will only grow. Combining innovation with the state’s long-standing values will create a distinct and dynamic cultural identity. ...Read more
 With ongoing investments in high-paying industries and skilled workforce education, Florida offers substantial development potential for entrepreneurs. However, in order to satisfy the demands of the region's diversified economy and provide opportunities, these firms rely on a workforce that requires improved education and training. Additionally, when combined with solid financial records, entrepreneurs choosing LLC status in Florida have advantageous tax laws that streamline their operations and increase their access to funding. One of the primary challenges startups face is securing the necessary capital to invest in their ventures. Economic downturns can further exacerbate this issue. Businesses should prioritize establishing robust accounts management systems that allow for consistent monitoring and tracking of cash flow. This not only helps in managing finances effectively but also makes the business more attractive to potential investors. Access to funding remains a primary concern for tech startups in Florida. While the state has seen increased venture capital investment in recent years, it lags behind traditional tech hubs like Silicon Valley. Startups often struggle to secure the necessary capital to scale their operations and compete on a larger scale. Developing a robust network of investors and venture capital firms is crucial to address this challenge. Economic uncertainty can significantly impact the growth prospects of startups. However, in recent years, Florida has become an appealing destination for startups due to its favorable climate and diverse economy. Despite past economic challenges, the state has witnessed a notable uptick in growth, making it an increasingly attractive option for entrepreneurs. Building a skilled workforce is a critical requirement for any business's success. Historically, high unemployment rates in Florida posed challenges in this regard. However, as employment rates have improved and tech companies have started relocating to the state, entrepreneurs have more opportunities to find and hire qualified talent. Investing in workforce development, particularly in finance, insurance, professional services, and healthcare sectors, can make startups more competitive. Lagging sales and competition from established businesses have been hurdles for startups. To secure a foothold in the market, startups need to consider increasing investments in infrastructure, such as plants and equipment. With the recent influx of tech companies from Silicon Valley, there is optimism about positive changes in Florida's business landscape. As the economy stabilizes, startups are becoming more open to these investments. Understanding and navigating tax regulations is essential for startups. Florida imposes taxes on corporations' income but generally exempts small businesses structured as LLCs, partnerships, or sole proprietorships from state income taxes. However, businesses may encounter changing tax regulations and filing requirements as they grow and evolve. Careful planning and compliance with tax regulations are crucial as startups transition into larger entities. While startups in Florida and across the United States face various challenges, they also have access to opportunities for growth and success. Establishing strong financial management practices, adapting to economic shifts, investing in a skilled workforce, making strategic infrastructure investments, and staying informed about tax regulations are all vital steps for startups to overcome obstacles and thrive in the competitive business environment. ...Read more
Due to the IT industry's constant evolution, entrepreneurs have several chances to develop novel products and expand upon established business strategies. Because they are the core hardware providers for the AI revolution, many tech businesses have risen to the top of worldwide value rankings. Computing is at the heart of almost every major tech company's product lines. Edge Computing: Edge computing refers to processing data in proximity to its source rather than depending on centralized data centers. This methodology minimizes latency and bandwidth consumption while improving data privacy. With the proliferation of IoT devices, the need for edge computing solutions is anticipated to rise. The inherently decentralized nature of this domain may foster an environment where numerous startups can capture portions of the market by offering specialized and niche solutions rather than allowing a single startup to dominate. The characteristic renders investments in the sector, at least theoretically, less precarious, which is encouraging for early-stage startups needing more support from significant computing corporations. Neuromorphic Computing: Neuromorphic computing seeks to re-create the human brain's neural architecture and operational mechanisms, thereby facilitating the development of more efficient and intelligent computing systems. This innovative approach promises to transform machine learning and robotics by offering power-efficient and adaptable solutions. Startups may concentrate on creating neuromorphic chips, software applications, or comprehensive systems. Serverless Computing: Serverless computing allows developers to create and operate applications without overseeing the underlying infrastructure. This methodology can decrease operational expenses and streamline deployment, making it a compelling choice for numerous enterprises. Startups have the opportunity to provide serverless platforms, tools, or services that assist businesses in embracing this model. Augmented Reality (AR) Cloud: The AR Cloud is a three-dimensional digital representation of the physical world, allowing for collaborative augmented reality experiences among various devices and users. This innovative technology promises to revolutionize the retail, gaming, real estate, and navigation sectors by offering engaging and interactive experiences. Entrepreneurs have the opportunity to create AR Cloud platforms, as well as content and tools that support the development and dissemination of augmented reality experiences. Federated Learning: Federated learning represents a collaborative approach to machine learning that facilitates the training of algorithms across various decentralized devices or servers while maintaining the confidentiality of raw data. This technique significantly improves privacy and security, allowing extensive, distributed datasets to be utilized. Startups have the opportunity to create federated learning frameworks, tools, or applications tailored to sectors that manage confidential information, such as healthcare and finance. ...Read more
The current business environment requires Asia Pacific organizations to make mental health a vital part of their strategic planning process. Employee wellbeing directly affects productivity levels, employee engagement, and all business results, according to increasing corporate recognition of this connection. The artificial intelligence solution has emerged as a major solution to mental health problems that arise from increased work demands and higher performance standards. Traditional mental health programs receive support from AI-driven tools, which provide evidence-based solutions and deliver scalable and individualized employee services to create a more resilient workforce. The implementation of these technological systems enables organizations to handle mental health issues through preventive methods, which create professional and personal development spaces for their staff members. How Can AI Identify Early Mental Health Challenges? The main benefit that AI provides to mental health treatment stems from its capacity to identify stress and burnout and other mental health issues during their beginnings. Machine learning algorithms can analyze patterns in workplace behavior, communication styles, and workload data to identify employees who may be at risk. AI systems operate continuously to detect potential problems that conventional assessment methods cannot achieve, thus enabling organizations to provide early support. Management teams use AI-driven insights to develop targeted initiatives such as workload adjustments and the allocation of specialized support resources. The ability of AI tools to provide objective evaluations helps organizations reduce human bias when assessing employee wellbeing needs. In this context, MySmax reflects how technology-driven solutions can support data-informed decision-making and workforce wellbeing strategies. These integrated systems deliver actionable intelligence that guides leadership decisions while maintaining employee confidentiality and building trust. What Strategies Ensure Effective AI Mental Health Integration? Organizations need to use a combination of strategic planning practices and ethical guidance methods, together with cultural awareness methods, to make AI mental health tools function effectively. Organizations must prioritize transparency in data usage, ensuring employees understand how their information is collected, processed, and protected. Organizations need to use system integration between their current human resources system and wellbeing initiative to establish an operational framework that combines both technological and human resource elements. Be Full supports workforce wellbeing and organizational alignment through structured approaches that enhance employee engagement and mental health strategies. Training managers to interpret AI-driven insights and respond empathetically strengthens organizational support structures. Cultural differences within the APAC region should be taken into account because different countries and industries hold distinct views about mental health. Businesses that address these considerations will enhance their AI solution effectiveness while building employee trust in the system. AI functions as a supporting technology that enhances organizational performance through its complementary relationship with human support systems. The technology provides organizations with data-driven solutions that help track, evaluate, and address their employees' mental health requirements. The artificial intelligence system enables APAC organizations to create adaptive and resilient workspaces, which help them deal with two major challenges: market competition and varied employee needs. Companies that combine technological advancements with human-centered approaches will create a workplace environment that actively promotes mental health while enabling employees to achieve their maximum professional capabilities. Organizations will achieve better operational performance and staff retention through AI mental health initiatives, which determine their success rate based on employee productivity measurements. ...Read more

Weekly Brief