Bain & Company has been recognized as a Leader, the highest category ranking a firm can receive, in The Forrester Wave: Innovation Consulting Services, Q2 2024. “Clients that seek holistic innovation advisory, anchored in a C-suite-mandated innovation strategy, are well placed to work with Bain,” wrote Forrester.

According to the report, Bain “has developed a sophisticated approach to organizational change, which was highly recognized by reference customers.” Reference customers also highlighted that Bain was “highly invested in their success, adapted quickly to their culture, and focused on capability building in the client organization.”

“We are thrilled to be recognized by Forrester as a leader in Innovation Consulting Services,” said Dunigan O’Keeffe,” a San Francisco based Partner and head of Bain’s global Strategy practice. “In today’s rapidly changing environment, having strong innovation capabilities is a strategic imperative for our clients as they pursue full potential.”

Forrester’s report also recognized Bain for following “a branded playbook for innovation strategy alignment, based on its “today forward and future back” approach, supporting organizations in articulating investment needs, opportunity spaces, and value propositions for innovation.”

According to the report, “Targeted at innovation portfolio derisking, Bain supports the full innovation lifecycle across the discover, validate, build, and commercialize phases.” It also found that to create sustainable delivery, “Bain emphasizes innovation ecosystems to drive informed ‘buy-partner-build’ decisions and art-of-the-possible experiences.”

“Innovation is a muscle that is challenging for many of our clients to build,” said O’Keeffe. “This recognition from Forrester reflects for us our commitment to helping our clients not only deliver on specific innovation projects, but also build ongoing innovation capabilities.”

Bain employs more than 1,500 in-house innovation delivery experts that provide world-class capabilities in new business innovation, product and experience innovation, automation, enterprise technology, software engineering and advanced analytics, including data science, machine learning and data engineering.

“Helping our clients solve their toughest innovation challenges requires integrated, interdisciplinary teaming,” said Arpan Sheth, a Partner and head of Bain’s global Innovation and Design capability. “We combine sector expertise and analytical rigor with innovation, design, engineering and technical experts in order to help our clients achieve their innovation goals.”

Forrester’s report further notes that: “…Bain emphasizes ecosystems and partnerships, most notably its AI impact alliance and venture ecosystem.” In recent years Bain has acquired or invested in several leading companies to enhance its innovation offerings. Bain’s latest acquisitions have included Umbrage, a Houston-based digital products studio working on state-of-the-art software solutions, Rainmaking APAC, a Singapore-based venture-building and start-up development studio, and Max Kelsen’s Australia-based AI engineering team. 

Additionally, the firm continues to expand its network of more than 700 ecosystem partners that provide access to new and emerging capabilities, including its global services alliance with OpenAI and a key partnership with Microsoft, enabling clients to deploy AI applications across their operations faster, more effectively and at scale.

“We have made significant investments in continuing to enhance our innovation talent and capabilities, both organically and through partnerships and acquisitions, and will continue doing so in the future,” said Sheth.

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Duetto (“Duetto” or the “Company”), a leading provider of revenue management software for the hospitality industry, today announced that it has been acquired by GrowthCurve Capital (“GrowthCurve”). GrowthCurve is acquiring the business from affiliates of Warburg Pincus and other shareholders. Terms of the transaction were not disclosed.

Duetto offers innovative solutions that simplify hotel operations and optimize revenue. With a focus on organic product development, data and integrations, Duetto connects disparate systems into a cohesive, efficient platform that drives profitability and growth for hotels worldwide. More than 6,000 hotel and casino resort properties in more than 60 countries use the Company’s applications, which include GameChanger for pricing, ScoreBoard for intelligent reporting, and BlockBuster for contracted-business optimization. Earlier this week, Duetto launched its newest product, OpenSpace, a revenue management solution and booking engine for meeting and event spaces. Duetto’s reliable customer service and unwavering commitment to simplifying the complexities of hotel revenue management have led to its recognition as the #1 RMS for three consecutive years by HotelTechAwards.

GrowthCurve Capital is a control-oriented private equity firm focused on building businesses by utilizing data, analytics and machine learning, combined with a comprehensive approach to human capital, to seek to accelerate growth and drive long-term value. GrowthCurve will partner with Duetto to further accelerate its AI strategy, including the development of new AI products, support the launch of new business lines and expand into new markets.

David Woolenberg, CEO of Duetto, stated, “We are excited to partner with GrowthCurve whose expertise in machine learning and AI, coupled with their experience in high-growth businesses, aligns perfectly with our vision. This acquisition will boost our investments in innovative tech, enhance our capabilities to support our customers and solidify our leadership in hotel revenue management. We thank our customers, team members, founders and partners for their continued support, as well as Warburg Pincus, Icon Ventures and our investors for their partnership. With the strength of the Duetto brand, we are confident that, together with GrowthCurve, we will achieve our ambitious growth objectives and drive the future of hospitality tech.”

Matthew Popper, Head of Technology and Information Services Investing at GrowthCurve, said, “Duetto is a leader in the fast-growing revenue management software market, with a differentiated solution that helps clients harmonize data and manage decision-making at scale. We look forward to partnering with David and the rest of the management team to accelerate Duetto’s growth, including applying GrowthCurve’s functional capabilities in data science and AI to further enhance the solution’s value proposition for clients.”

Sim Allan, Vice President at GrowthCurve, added, “Duetto is uniquely positioned to accelerate the adoption of sophisticated analytics and AI in the hospitality sector, enabling clients to unlock the value of their data for all stakeholders, including enhancing guest experiences. We are excited to partner with David and the industry-leading team at Duetto to continue delivering innovative software solutions to the hospitality sector.”

“It has been a privilege and a pleasure to partner with Duetto these past seven years. Duetto’s relentless focus on customer satisfaction has been key to its success,” said Ash Somani and Parag Gupta, Managing Directors at Warburg Pincus. “Under David Woolenberg’s leadership, Duetto has built an incredibly talented team that we are confident will continue to thrive in its next phase of growth.”

Jefferies LLC served as lead financial advisor, William Blair served as an advisor, and Orrick, Herrington & Sutcliffe LLP served as legal counsel to Duetto. Houlihan Lokey served as exclusive financial advisor and Davis Polk & Wardwell served as legal counsel to GrowthCurve.

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DataRobot, the enterprise AI platform, today announced it was named a Leader in the Gartner Magic Quadrant for Data Science and Machine Learning (DSML) Platforms.¹ The evaluation was based on specific criteria that analyzed the company’s overall completeness of vision and ability to execute. Of the 18 vendors evaluated in the report, DataRobot received the highest ranking for Governance Use Case (4.10/5).²

“DataRobot revolutionized machine learning with an enterprise-scale AI platform focused on helping organizations leverage AI in a way that is right for their business,” said Debanjan Saha, Chief Executive Officer, DataRobot. “We believe that our recognition as a Leader showcases the strength of our technology and continuous innovation. The DataRobot AI Platform and its governance capabilities are the definitive solution for the enterprise, and we’ll continue to deliver the cutting-edge capabilities our customers require to drive business impact.”

The DataRobot AI Platform is built for the modern enterprise, enabling AI teams to collaboratively build, deploy and govern enterprise-grade AI solutions safely and with confidence. As the leading AI platform, DataRobot unifies diverse tools, teams, and infrastructure. The platform is designed for flexibility and optionality, making it easy for organizations to leverage existing investments and deploy AI anywhere — from the edge to within applications.

A Gartner Magic Quadrant is a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors. A Magic Quadrant provides a graphical competitive positioning of four types of technology providers, in markets where growth is high and provider differentiation is distinct: Leaders, Challengers, Visionaries and Niche Players. This research helps data and analytics leaders make critical decisions selecting a DSML platform vendor.

Additional Resources

To learn more about DataRobot’s recognition in the 2024 Gartner Magic Quadrant for DSML, please visit our website.

To learn more about the DataRobot AI Platform and its governance capabilities, please register for the webinar “Governance in the Era of AI” on July 23.

¹Source: Gartner Magic Quadrant for Data Science and Machine Learning Platforms, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Raghvender Bhati, Maryam Hassanlou, Tong Zhang, June 17, 2024.

²Source: Gartner Critical Capabilities^TM for Data Science and Machine Learning Platforms, Machine Learning (ML) Engineering, Afraz Jaffri, Aura Popa, Peter Krensky, Jim Hare, Tong Zhang, Maryam Hassanlou, Raghvender Bhati, Published June 24, 2024.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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Introduction

The business landscape has been transformed over the past few years with the help of numerous technologies, and one such marvel is augmented intelligence, which has emerged as a potent ally for human users to enhance our business capabilities. This technology represents a synergy between human expertise and machine learning (ML), redefining how human intelligence approaches problem-solving, decision-making, and innovation. However, amidst all the insights, it is essential to understand that augmented intelligence is not a solution that can be operated independently. Still, it requires human oversight and intervention to help carefully orchestrate ethical considerations to ensure their alignment with human values and ideals.

In today’s AI Tech Park article, we will explore the boundless potential of augmented intelligence in reshaping the future of business.

A Symbiotic Relationship with Organizations and Augmented Intelligence

Augmented intelligence focuses on enhancing human capabilities by combining creativity and design-making skills with artificial intelligence’s (AI) ability to process large sets of data in a few seconds. For instance, in the healthcare sector, AI filters through millions of medical records to assist doctors in diagnosing and treating patients more effectively, therefore not replacing doctors’ expertise but augmenting it. Further, AI automates repetitive tasks, allowing human users to tackle more complex and creative work, especially with chatbots as they handle routine inquiries in customer service, allowing human agents to resolve more minute issues.

Augment intelligence uses personalized experience at a scale that informs users about current market trends, enhancing customer satisfaction, further helping to stimulate human creativity, and exploring new patterns and ideas. Numerous tools, such as OpenAI’s GPT-4 and Google Gemini, can create high-quality written content, which will assist writers and marketers in inefficiently generating social media posts and creative writing pieces. In terms of designing, genAI tools such as DALL-E and MidJourney work as guides that enable designers to generate unique images and artwork based on a few textual descriptions.

Real-World Business Scope of Augmented Intelligence

Till now, we have understood that augmented intelligence is the next thing that companies should implement in their businesses to kickstart a creative yet partially autonomous journey. Therefore, we bring you some key areas where augmented intelligence can have a significant impact:

1. Retail and Manufacturer Industry

The retail industry has witnessed a change in customer tastes post-COVID-19 pandemic, disrupting their logistical and supply chain structures. Therefore, retailers utilize augmented intelligence to analyze customer preference, purchase history, and browsing human behavior to deliver personalized product recommendations that not only enhance their shopping experience but also drive more sales and foster customer loyalty. On the other hand, the manufacturing industry has faced challenges such as supply chain disruptions, a massive drop in worker supply, and raw material shortages due to the pandemic and recession. Therefore, to curb these issues, B2B manufacturers rely on augmented intelligence that aids in data collection from sensors and IoT devices, which eventually helps them understand the production capacities of the production lines, the shipping times, warehousing space availability, and scheduling time for the workers.

2. Healthcare Industry

With the rise in patient personalization and medical and drug experiments, healthcare providers are leveraging augmented intelligence to analyze the largest amount of medical data and predict and diagnose diseases more accurately and efficiently. With the help of augmented analytics, hospitals and medical institutes can optimize their business operations by researching key metrics such as the duration of stay and the bed occupancy rate.

Bottom Line

The human-AI collaboration offers potential by leveraging the strengths of both human creativity and augmented intelligence to achieve shared objectives of better business operations. However, the implementation of this technology doesn’t imply the replacement of human intelligence, but this collaborative initiative will enhance decision-making, boost efficiency, and transform business interaction to enhance organization scalability and personalization.

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Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, today announced the general availability of LLM Observability, which allows AI application developers and machine learning (ML) engineers to efficiently monitor, improve and secure large language model (LLM) applications. With LLM Observability, companies can accelerate the deployment of generative AI applications to production environments and scale them reliably.

Organizations across all industries are racing to release generative AI features in a cost-effective way, but implementing and bringing them to production can present several challenges due to the complexity of LLM chains, their non-deterministic nature and the security risks they pose.

Datadog LLM Observability helps customers overcome these challenges so they can confidently deploy and monitor their generative AI applications. This new product provides visibility into each step of the LLM chain to easily identify the root cause of errors and unexpected responses such as hallucinations. Users can also monitor operational metrics like latency and token usage to optimize performance and cost, and can evaluate the quality of their AI applications—such as topic relevance or toxicity—and gain insights to mitigate security and privacy risks with out-of-the-box quality and safety evaluations.

Unlike traditional tools and point solutions, Datadog’s LLM Observability offers prompt and response clustering, seamless integration with Datadog Application Performance Monitoring (APM), and out-of-the-box evaluation and sensitive data scanning capabilities to enhance the performance, accuracy and security of generative AI applications while helping to keep data private and secure.

“WHOOP Coach is powered by the latest and greatest in LLM AI. Datadog’s LLM Observability allows our engineering teams to evaluate performance of model changes, monitor production performance and increase quality of Coach interactions. LLM Observability allows WHOOP to provide and maintain coaching for all our members 24/7,” said Bobby Johansen, Senior Director Software at WHOOP.

“The Datadog LLM Observability solution helps our team understand, debug and evaluate the usage and performance of our GenAI applications. With it, we are able to address real-world issues, including monitoring response quality to prevent negative interactions and performance degradations, while ensuring we are providing our end users with positive experiences,” said Kyle Triplett, VP of Product at AppFolio.

“There’s a rush to adopt new LLM-based technologies, but organizations of all sizes and industries are finding it difficult to do so in a way that is both cost effective and doesn’t negatively impact the end user experience,” said Yrieix Garnier, VP of Product at Datadog. “Datadog LLM Observability provides the deep visibility needed to help teams manage and understand performance, detect drifts or biases, and resolve issues before they have a significant impact on the business or end-user experience.”

LLM Observability helps organizations:

• Evaluate Inference Quality: Visualize the quality and effectiveness of LLM applications’ conversations—such as failure to answer—to monitor any hallucinations, drifts and the overall experience of the apps’ end users.
• Identify Root Causes: Quickly pinpoint the root cause of errors and failures in the LLM chain with full visibility into end-to-end traces for each user request.
• Improve Costs and Performance: Efficiently monitor key operational metrics for applications across all major platforms—including OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, Vertex AI and more—in a unified dashboard to uncover opportunities for performance and cost optimization.
• Protect Against Security Threats: Safeguard applications against prompt hacking and help prevent leaks of sensitive data, such as PII, emails and IP addresses, using built-in security and privacy scanners powered by Datadog Sensitive Data Scanner.

Datadog LLM Observability is generally available now. To learn more, please visit: http://datadoghq.com/product/llm-observability.

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The acquisition will provide significant benefits to both companies’ customer bases. Simplify Healthcare’s established cloud based platform – Simplify Health Cloud, combined with Virtical.ai’s innovative AI platform, will create a powerful suite of tools that unlock new levels of innovation, efficiency, and growth enablers at Payers. By leveraging the power of AI for data extraction and comparison using an AI model trained on thousands of Health Plan specific documents such as the SBC (Statement of Benefits and Coverage), the Virtical.ai platform enables Payers to offer hyper-personalized plans and benefits to their members in employer and individual segments. This empowers a Payer’s broker community as well to serve their mutual customers with the most optimum offerings, ultimately serving members.

Additionally, the Virtical platform assists in identifying gaps in Payer networks — holistically as well as by customer and prospect — by comparing provider and member locations, allowing Payers to strategically promote their network coverage strengths as well as address deficiencies to ensure members have access to adequate providers within their area. Payers can also compare negotiated provider rates with those of their competitors, helping them to gain insight into how their rates stack up against other networks and where to immediately target marketing spend.

Mohammed Vaid, CEO of Simplify Healthcare, expressed his enthusiasm for the acquisition, stating, “We are thrilled to welcome Virtical.ai to the Simplify Healthcare family. This strategic move underscores our unwavering commitment to AI and its potential to transform how Payers operate. Together, we will equip our customers with the tools they need to seamlessly integrate AI into their workflows and unlock its full potential. With AI models that are able to consume and make sense of the complex documents at Payers, such as SBCs to radically transform plan comparison and selection; and ingest the hard to understand Machine Readable Files (MRFs) around price transparency, we will now be able to fuel the growth strategies for Payers. In concert with the Simplify Health Cloud, this creates a crucial value proposition for our customers. I am excited about the tremendous value we can bring to Payers, together with Deepak and his team.”

Vinay Nadig, Chief Strategy Officer at Simplify Healthcare, echoed this sentiment, highlighting the acquisition’s role in executing the company’s vision. “This acquisition represents a significant step forward in our strategic roadmap. By combining Simplify Healthcare’s industry-leading platform with Virtical.ai’s cutting-edge AI innovations in both Health Plan Sales Solutions and Network Management Solutions, we will empower Payers to achieve growth even as they face disruptive market and regulatory forces. Using both GenAI and Machine Learning (ML) algorithms on unstructured document content (such as SBCs, EOCs, etc.) as well as structured data (price transparency MRFs, Geo data, etc.), we will be able to deliver outstanding solutions to Payers as they grapple with harnessing the power of AI to serve their members.”

Deepak Bandi, CEO of Virtical.ai, expressed his excitement about joining forces with Simplify Healthcare. “We are incredibly excited to embark on this journey with Simplify Healthcare. The combined strength of our teams and technologies represents a game-changer for Payers. We share a common vision for empowering businesses with AI, and together, we will accelerate its adoption and unlock its transformative potential. Our AI models, built on multiple decades of learning and experience at Payers and positioned to drive membership growth and revenue, in conjunction with Simplify Healthcare’s enterprise SaaS platform, will provide a tremendous competitive advantage to Payers. I look forward to working with Mohammed and Vinay to amplify our collective value to our customers.”

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• chipIgnite platform has fueled the creation of new vertical solutions, empowering mission-driven companies
• More than 1,400 designs developed to date by entrepreneurs and innovators

Efabless Corporation, the creator platform for chips, is excited to announce that it has enabled 40 new companies to design chips.

While governments worldwide are investing billions of dollars in production capacity, the semiconductor industry faces consolidation. Simultaneously, there is a rapidly growing demand for new designs to meet the surge of applications driven by secure, energy optimized, machine learning applications.

Efabless is addressing this design gap by making chip design affordable, simple, and accessible. It provides a capital efficient path for new semiconductor companies and enables product companies to create chips that go into smarter and better products. Efabless broadens the community of potential chip designers by 100x, fostering innovation, research, and development in new applications for semiconductors.

By democratizing access to chip design and manufacturing, Efabless is driving the creation of new industries and verticals that will shape the future of technology and innovation. From agriculture, industrial, infrastructure, smart home appliances to quantum computing, aerospace, security, autonomous vehicles, and medical devices, Efabless is enabling entrepreneurs and innovators to develop cutting-edge technologies that are transforming industries and improving lives.

How Efabless Makes It Possible:

Efabless brings software-style open-source and community models to chip creation, fostering a vibrant community of designers and engineers who collaborate, share designs and IP, and support one another. Efabless provides a comprehensive, user-friendly platform that simplifies the entire chip design and manufacturing process.

• Marketplace: The platform includes an extensive marketplace of reusable IP blocks and reference designs allowing designers to quickly assemble and customize their chip designs.
• Access to Design Tools: Efabless provides design tools, code, and verification examples accessible through its platform, eliminating the need to develop from scratch.
• Supply Chain: Once a design is finalized, Efabless manages the supply chain for fabrication, assembly and testing processes, leveraging its partnerships with leading vendors to ensure high-quality production.
• Cost Efficiency: By streamlining the design-to-manufacturing pipeline, Efabless significantly reduces the cost and time required to bring a custom chip to market, making it accessible to startups and small companies.

Recent customers utilizing Efabless’s platform include companies in sensor applications, IoT and industrial controllers, and security, all developing innovative solutions for various applications. Additionally, as part of research projects, chips for AI and medical devices are being created.

“Efabless chipIgnite has been an invaluable tool for broadening participation in chip design. The open-source foundation provides a transparent and accessible platform for users with varying levels of experience, allowing them to delve deeper into the core concepts and focus on design creativity and innovation. chipIgnite will continue to play a critical role in a mature ecosystem that needs new impulses for nurturing the next generation of chip designers,” said Boris Murmann. Professor, University of Hawaii and Chair, IEEE SSCS Technical Committee on the Open-Source Ecosystem.

“With the chip industry consolidating, we are excited to reverse the trend by enabling the next generation of chip creators,” said Mike Wishart, CEO of Efabless. “This includes new startups achieving proof of concept to raise funds and secure initial customers, as well as product companies designing chips for new applications. Our platform lowers the threshold for new initiatives, empowering entrepreneurs to create their own chips, start businesses, and generate economic value.”

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H2O.ai, the leading open source Generative AI and machine learning platform, today announced the appointment of Agus Sudjianto as Senior Vice President, Risk and Technology for Enterprise. Agus brings over two decades of experience in the financial services industry, where he has held leadership positions at Wells Fargo and Bank of America in risk management, analytics, and modeling.

Agus is renowned for pioneering the first of its kind PiML (Python Interpretable Machine Learning) as a set of methods and tools in Python aimed at making machine learning models interpretable and understandable to humans. He championed the adoption of PiML at Wells Fargo and subsequently released it under Apache 2.0 to democratize models for ensuring reliability, resilience, and fairness in high-risk applications across banks and financial institutions. Agus’ PiML is now widely adopted across many industries and has become the industry standard for developing interpretable machine learning models that provide transparency and improve trust.

“Agus is a global treasure and a leader in building trust and regulating models in banking, finance, insurance and regulated industries. Agus has been inspiring the H2O.ai community and customers with his genius and knack for interpreting deep concepts for any audience. Super excited to have Agus join my leadership team to bring the rigor of MRM to GenAI with innovative products and to make AI trustworthy for our customers and accelerate our mission to democratize AI in the service of life and the planet.” – Sri Ambati, CEO and Founder of H2O.ai.

“I am thrilled to join H2O.ai, a company deeply committed to making AI safe, reliable, and accessible to all. I look forward to leveraging my experience in risk management and PiML to develop H2O Eval products, expand Responsible AI initiatives, and foster a community dedicated to building trust in Generative AI applications, particularly in banking and model risk management,” said Agus Sudjianto, Senior Vice President, Risk and Technology for Enterprise at H2O.ai.

Agus holds a PhD in Engineering from Wayne State University and a Master’s degree from MIT. At H2O.ai, he will develop H2O Eval products to address AI safety, reliability and compliance, focusing on Generative AI applications in banking and model risk management. He will also expand the company’s Responsible AI initiatives.

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Table of content
Introduction
1. Yellowfin
2. Sisense
3. QlikView
4. Kyligence
5. Tableau
Winding Up

Introduction

In this digital age, data is the new oil, especially with the emergence of augmented analytics as a game-changing tool that has the potential to transform how businesses harness this vast technological resource for strategic advantages. Earlier, the whole data analysis process was tedious and manual, as each project would have taken weeks or months to get executed. At the same time, other teams had to eagerly wait to get the correct information and further make decisions and actions that would benefit the business’s future. 

Therefore, to pace up the business process, the data science team required a better solution to make faster decisions with deeper insights. That’s where an organization needs to depend on tools such as augmented analytics. Augmented analytics combines artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to enhance the data analytics processes, making them more accessible, faster, and less prone to human error. Furthermore, augmented analytics automates data preparation, insight generation, and visualization, enabling users to gain valuable insights from data without extensive technical expertise. 

In today’s exclusive AITech Park article, we will take a quick look at the top five augmented analytics tools that data scientist teams can depend on to democratize advanced-level analytics with augmented data ingestion, data preparation, analytics content, and DSML model development. 

1. Yellowfin

Yellowfin specializes in dashboards and data visualization that have inbuilt ML algorithms that provide automated answers in the form of an easy guide for all the best practices in visualizations and narratives. It has a broad spectrum of data sources, including cloud and on-premises databases such as spreadsheets, which enables easy data integration for analysis. The platform comes pre-built with a variety of dashboards for data scientists that can embed interactive content into third-party platforms, such as a web page or company website, allowing users of all expertise levels to streamline their business processes and report creation and sharing. However, when compared to other augmented analytics tools, Yellowfin had issues updating the data in their dashboard on every single update, which poses a challenge for SMEs and SMBs while managing costs and eventually impacts overall business performance. 

2. Sisense

Sisense is one of the most user-friendly augmented analytics tools available for businesses that are dealing with complex data in any size or format. The software allows data scientists to integrate data and discover insights through a single interface without scripting or coding, allowing them to prepare and model data. Eventually allows chief data officers (CDOs) to make an AI-driven analytics decision-making process. However, the software is extremely difficult to use, with complicated data models and an average support response time. In terms of pricing, Sisense functions on a subscription pricing model and offers a one-month trial period for interested buyers; however, the exact pricing details are not disclosed. 

3. QlikView

QlikView is well-known for its data visualization, analytics, and BI solution that aids IT organizations in making data-based strategic decisions with the help of sophisticated analytics and insights drawn from multiple data sources. The platform allows data scientists to develop, extend, and embed visual analytics in existing applications and portals while adhering to governance and security frameworks. However, some users have reported that the software may slow down when assembling large datasets. Additionally, the software sometimes lacks the desired feature and depends mostly on plugins from the older QlikView, which lacks compatibility with the updated Qlik Sense. The QlikView comes in three pricing plans: Standard Plan: $20/mo for 10 full users only, with up to 50GB/year data for analysis, Premium Plan: starts at $2,700/mo and 50GB/yr data for analysis and more advanced features and  Enterprise Plan: Custom pricing, starting at 500GB/yr data for analysis.

4. Kyligence

The fourth augmented analytics tool that data scientist teams use is Kyligence, as it stands out for its automated insights and NLP technology for businesses to generate deep insights within seconds. The technology also promises a centralized, low-code platform that emphasizes a metrics-driven approach to business decision-making and further identifies the ups and downs of the given metrics, along with discovering root causes and generating reports within seconds. However, the tools are considered to be quite complex and expensive when compared to other augmented analytics tools on the market. Kyligence comes in three pricing plans. Standard plan: $59/user/month, Premium plan: $49/user/month (minimum 5 users), and Enterprise+ plan: Flexible pricing and deployment options.

5. Tableau

Last but not least, we have the famous Tableau, an integrated BI and analytics solution that will help in acquiring, producing, and analyzing the company’s data and provide insightful information. Data scientists can use Tableau to collect information from a variety of sources, such as spreadsheets, SQL databases, Salesforce, and cloud applications. Talking about the interface, it is quite easy regardless of your technical skills, allowing you to explore and visualize data effortlessly, but professionals at an executive level might have issues adapting to this technology. However, the most concerning part of this software is its high pricing and lack of customization in terms of visualization options. In terms of pricing, Tableau comes with two exclusive plans: for an individual user, it is $75/month, and for two users, it is $150/month.

Winding Up

With the importance of data, data analytics, and augmented analytics tools, data scientists are paving the way for effortless and informed decision-making. The five tools listed above are designed to automate the complex data analysis process.

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“Elisa is a bridge between advanced technology and our customers, providing them with instant access to marketplace information and a conversational interface that understands their research needs,” said Chris Petersen, Founder and CTO of Scientist.com. “It’s the latest in a series of LLM-powered tools we’ve built to help life science researchers run their drug discovery programs faster and at lower cost.”

Elisa addresses three key challenges for pharma and biotech companies integrating large language models into their operations:

1. It guarantees complete privacy and confidentiality of all data.

2. It provides a cost-efficient solution with the capabilities and flexibility of high-end platforms like Azure or Amazon.

3. It eliminates the need for extensive technical expertise to develop and operate a private LLM on your own infrastructure.

Other LLM-enabled tools on the Scientist.com marketplace help marketplace users negotiate pricing with suppliers, respond quickly to supplier messages, find services and products, and understand legal agreements.

The company also uses machine learning algorithms trained on nearly a decade of marketplace data to create proprietary predictive models that help researchers find and evaluate the best technology and labs for their research needs as well as forecast supplier performance once the research project is initiated. These include the Tumor Model Finder^TM, which compares DNA sequencing data on 10,000 oncology models to help researchers identify and purchase the most appropriate model.

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