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Augmented Analytics: The Next-Big Thing in Data Analytics

Augmented Analytics: The Next-Big Thing in Data Analytics
The next significant wave in data and analytics will empower businesses to achieve business value quicker, more effectively, and on a far wider scale. The integration of artificial intelligence and predictive analytics alters the way analytical material is produced, consumed, and shared. Yes, we are discussing augmented analytics. Augmented analytics assists in digging deeper into the "why" of the result and produces more accurate predictions.

Augmented Analytics: A Valuable Tech for Businesses



How Augmented Analytics Empowers Marketers in Making Better Decisions and Converting Prospects

Marketing teams all across the globe are battling with frozen or declining budgets, yet they are still expected to generate pipelines and increase revenue. The great news is that, due to the advantages of augmented analytics, marketers no longer have to depend just on gut sense, previous experience, estimations, or trial and error. Instead, they can depend on data-driven marketing choices that are based on insights generated by augmented analytics.

  • Augmented analytics uses AI and ML to discover key drivers and helps marketers understand why metrics change.
  • Augmented analytics provides recommendations and actionable insights to marketers and helps them improve campaign outcomes.
  • Augmented analytics reduces time-to-insight by automatically surfacing actionable insights on various customer data points to increase conversion and win.
  • Augmented analytics minimize human work and turnaround time on insights, assisting marketers in recognizing areas of greatest potential and increasing ROI on marketing expenditures.
  • According to Salesforce Research, the top reason marketers embraced AI in 2021 was to drive the next best actions. That is exactly what augmented analytics offers marketers: the ability to provide actionable insights to teams.


Closing Notes

Every day, the incredible rise of IoT devices generates massive amounts of data. The AI-powered analytical tools can extract the maximum value from the data.

Spotlight

Silver Touch Technologies Ltd

IT company active in Software Outsourcing, IT Consulting, System Integration. Having global presence for service delivery in USA, UK and France. Work with global brand leaders like SAP, Oracle, Microsoft, IBM to provide IT solution and integration services. Unique Software outsourcing model called - Global Application Delivery Model (GADM) to serve client across the world.

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Business Intelligence, Big Data Management, Big Data

BI Performance Metrics to Scrutinize Your Business Strategy

Article | July 10, 2023

The top-performing companies use data to navigate their way, and there's absolutely no reason why you shouldn't do the same with your business choices. Key performance indicators (KPIs) in business intelligence enable you to get insight into the overall health of your organization, any of your departments, or even how your consumers view your company. And you don't have to play the BI game manually anymore. You only need to invest in a good business intelligence platform to weave the magic figures for you, a feat that was formerly extremely constrained or even forbidden. If you are knowledgeable enough, you should be able to determine which business intelligence tools are best suited to your particular requirements. In this article, we will provide some of the most important business intelligence key performance indicators (KPIs) to give you a head start in analyzing how your company aligns with the objectives you have set for it at any point in time. Business Intelligence Key Performance Indicators for Evaluating Business Strategies Financial Metrics The most important metric of all. To calculate your financial metrics, you must look at your cash flow, balance sheet, and income statement using a tool such as your accounting software. Any of these criteria should tell you whether your company is financially sound, which indicates it is producing income and managing its finances well. If you want to push your company on a new growth path or spark the attention of possible investors, you will offer them these financial KPIs as evidence of investment value. Example: Liquidity Ratio Net Income vs. Net Earnings Working Capital Debt to Equity Ratio Marketing Metrics In terms of business effectiveness, marketing metrics rank second only to financial metrics. Marketing metrics show the data that tells you if your most recent marketing initiatives are achieving the results you expected. Capable marketing software tools must provide you with values, such as your new content strategy riding your most recent marketing initiatives across numerous platforms. Example: Customer Acquisition Cost (CAC) Conversion Rate Average Spend Per Customer Project Management Metrics If your finances and marketing expenses are in order, it could simply be because your production departments are working hard to complete projects on time or ahead of schedule, under budget, and while keeping both clients and employees satisfied. But what should be measured to know where everything moved at the end of the day or year? As a company owner or business leader, you should consider your productivity, profit margins, ROI, customer satisfaction, and earned value, among other things—all of which can be easily obtained from any of the top project management systems. Example: Return on Investment (ROI) Productivity Customer Service Metrics When you consider that 89% of U.S. consumers have moved to a company competitor after a bad experience, it is evident that any customer service metrics have to go beyond operational information and include how your customer service team engages with your customers. Experience data acknowledges the personal human aspect at the heart of company and customer relationships, enabling you to discover how your consumers value their interactions with your customer service executives. Example: Customer Effort Score (CES) Net Promoter Score (NPS) Closing Lines Business intelligence is an essential technology that provides crucial information about a company's operations. Identifying which aspects of your organization are performing well is one thing; ensuring that they continue to do so while addressing those that are struggling to stay up and meet your aims is another. Business intelligence solutions allow you to assess performance, identify shortcomings, and develop plans to increase workflow effectiveness and customer engagement.

Read More
Business Intelligence, Big Data Management, Data Science

Put Publicly Available COVID-19 Data to Work for Your Business—Fast

Article | April 13, 2023

There’s a lot of information out there related to COVID-19. But right now—when it’s more important than ever to quickly access and analyze data —figuring out how to effectively use COVID-19 data to better manage your business can still be a challenge. We can help. Several customers have leveraged their Incorta platforms to instantaneously integrate COVID-19 data into their enterprise data and analytics dashboards.

Read More
Big Data Management, Data Science, Big Data

Embrace Business Intelligence to Boost Your Revenue

Article | May 16, 2023

Managing and marketing a successful company cannot be done by guesswork. Your instincts can lead you a long way, but data will always get you further. You can substantially enhance your strategic decision-making and future direction with the correct analytics approach and business intelligence. It is not always simple. Data gathering is challenging enough, but understanding that data becomes even more complicated. However, the advantages of using this sort of data-driven strategy much exceed the challenges. Let's take a closer look at the significance of business intelligence and how it can help your organization succeed in the short and long term. How Business Intelligence Can Help You Increase Sales and Revenue A BI tool can make it much simpler for your sales representatives to comprehend their customer base by allowing them to gather, unify, and analyze their data all in one spot. Here are some ways your sales team will thrive with the use of business intelligence. Share Sales Analytics Across Divisions Easily You can simply construct dashboards that give insights into the sales team's important indicators and interactive reports that can be shared across departments using a BI tool. The marketing team would be able to identify which campaigns are generating sales, while the operations team would be able to prepare for and estimate product demand. Additionally, depending on sales activity, management would be able to execute more precise business decisions. Accurate Sales Forecasts Companies that foresee future trends and performance have a competitive edge since it allows you to be agile. A BI solution unifies and simplifies all of your data, providing you with the most precise and up-to-date information. Having access to all of your previous sales trends in one location makes it simpler to correctly forecast future income and sales. By removing the difficulties of collecting past and current data in one place, your team can create more realistic goals, which can be tough if your sales performance is dependent on factors such as the month, client segments, and so on. Improves Customer Retention It is a known fact that offering and selling your services or goods to an existing customer is cheaper than acquiring new customers, who might cost up to seven times more. A BI system can assist a company's sales team in understanding what drives current customers and what they purchase, tracking demand patterns, and recognizing chances to cross-sell, which can then be utilized to create sales efforts. Closing Lines Utilizing business intelligence effectively can assist your business in improving customer retention, increasing income from sales efforts, and keeping your sales analytics up-to-date. As sales drive company development, a business intelligence solution like Power BI might be one of the most important investments you make. Business intelligence, whether for a major corporation or a small business, can provide your sales force with the competitive advantage it needs to stay ahead.

Read More
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Why Adaptive AI Can Overtake Traditional AI

Article | July 12, 2022

With the ever-changing technology world, company demands and results are no longer the norm. Businesses in a variety of sectors are using artificial intelligence (AI) technologies to solve complicated business challenges, build intelligent and self-sustaining solutions, and, ultimately, remain competitive at all times. To that aim, ongoing attempts are being made to reinvent AI systems in order to do more with less. Adaptive AI is a significant step in that direction. It has the potential to outperform standard machine learning (ML) models in the near future because of its ability to enable organizations to get greater results while spending less time, effort, and resources. The capacity of adaptive AI to enable enterprises to achieve greater outcomes while investing less time, effort, and assets is why it can overtake traditional AI models. Why Adaptive AI Overtakes Traditional AI Robust, Efficient and Agile Robustness, efficiency, and agility are the three basic pillars of Adaptive AI. The ability to achieve great algorithmic accuracy is referred to as robustness. The capacity to achieve reduced resource utilization is referred to as efficiency (for example, computer, memory, and power). Agility manages the ability to change operational circumstances in response to changing demands. Together, these three Adaptive AI principles provide the groundwork for super-capable AI inference for edge devices. Data-Informed Predictions A single pipeline is used by the adaptive learning approach. With this method, you can use a continually advanced learning approach that maintains the framework up-to-date and encourages it to achieve high levels of performance. The Adaptive Learning method examines and learns new changes made to the information and produces values, as well as their associated attributes. Moreover, it benefits from events that can modify market behavior in real-time and, as a result, maintains its accuracy consistently. Adaptive AI recognizes information from the operational environment and uses it to produce data-informed predictions. Closing Lines Adaptive AI will be utilized to meet changing AI computing requirements. Operational effectiveness depends on algorithmic performance and available computer resources. Edge AI frameworks that can change their computing demands effectively reduce compute and memory requirements. Adaptive AI is robust in CSPs' dynamic software environments, where inputs and outputs alter with each framework revamp. It can assist with network operations, marketing, customer service, IoT, security, and customer experience.

Read More
Business Intelligence, Big Data Management, Big Data

Implementing Data Analytics: Emerging Big Data Tools in 2023

Article | July 10, 2023

The top-performing companies use data to navigate their way, and there's absolutely no reason why you shouldn't do the same with your business choices. Key performance indicators (KPIs) in business intelligence enable you to get insight into the overall health of your organization, any of your departments, or even how your consumers view your company. And you don't have to play the BI game manually anymore. You only need to invest in a good business intelligence platform to weave the magic figures for you, a feat that was formerly extremely constrained or even forbidden. If you are knowledgeable enough, you should be able to determine which business intelligence tools are best suited to your particular requirements. In this article, we will provide some of the most important business intelligence key performance indicators (KPIs) to give you a head start in analyzing how your company aligns with the objectives you have set for it at any point in time. Business Intelligence Key Performance Indicators for Evaluating Business Strategies Financial Metrics The most important metric of all. To calculate your financial metrics, you must look at your cash flow, balance sheet, and income statement using a tool such as your accounting software. Any of these criteria should tell you whether your company is financially sound, which indicates it is producing income and managing its finances well. If you want to push your company on a new growth path or spark the attention of possible investors, you will offer them these financial KPIs as evidence of investment value. Example: Liquidity Ratio Net Income vs. Net Earnings Working Capital Debt to Equity Ratio Marketing Metrics In terms of business effectiveness, marketing metrics rank second only to financial metrics. Marketing metrics show the data that tells you if your most recent marketing initiatives are achieving the results you expected. Capable marketing software tools must provide you with values, such as your new content strategy riding your most recent marketing initiatives across numerous platforms. Example: Customer Acquisition Cost (CAC) Conversion Rate Average Spend Per Customer Project Management Metrics If your finances and marketing expenses are in order, it could simply be because your production departments are working hard to complete projects on time or ahead of schedule, under budget, and while keeping both clients and employees satisfied. But what should be measured to know where everything moved at the end of the day or year? As a company owner or business leader, you should consider your productivity, profit margins, ROI, customer satisfaction, and earned value, among other things—all of which can be easily obtained from any of the top project management systems. Example: Return on Investment (ROI) Productivity Customer Service Metrics When you consider that 89% of U.S. consumers have moved to a company competitor after a bad experience, it is evident that any customer service metrics have to go beyond operational information and include how your customer service team engages with your customers. Experience data acknowledges the personal human aspect at the heart of company and customer relationships, enabling you to discover how your consumers value their interactions with your customer service executives. Example: Customer Effort Score (CES) Net Promoter Score (NPS) Closing Lines Business intelligence is an essential technology that provides crucial information about a company's operations. Identifying which aspects of your organization are performing well is one thing; ensuring that they continue to do so while addressing those that are struggling to stay up and meet your aims is another. Business intelligence solutions allow you to assess performance, identify shortcomings, and develop plans to increase workflow effectiveness and customer engagement.

Read More
Business Intelligence, Big Data Management, Data Science

Navigating Big Data Integration: Challenges and Strategies

Article | April 13, 2023

There’s a lot of information out there related to COVID-19. But right now—when it’s more important than ever to quickly access and analyze data —figuring out how to effectively use COVID-19 data to better manage your business can still be a challenge. We can help. Several customers have leveraged their Incorta platforms to instantaneously integrate COVID-19 data into their enterprise data and analytics dashboards.

Read More
Big Data Management, Data Science, Big Data

The Future of Big Data: Trends and Innovations for 2023 and Beyond

Article | May 16, 2023

Managing and marketing a successful company cannot be done by guesswork. Your instincts can lead you a long way, but data will always get you further. You can substantially enhance your strategic decision-making and future direction with the correct analytics approach and business intelligence. It is not always simple. Data gathering is challenging enough, but understanding that data becomes even more complicated. However, the advantages of using this sort of data-driven strategy much exceed the challenges. Let's take a closer look at the significance of business intelligence and how it can help your organization succeed in the short and long term. How Business Intelligence Can Help You Increase Sales and Revenue A BI tool can make it much simpler for your sales representatives to comprehend their customer base by allowing them to gather, unify, and analyze their data all in one spot. Here are some ways your sales team will thrive with the use of business intelligence. Share Sales Analytics Across Divisions Easily You can simply construct dashboards that give insights into the sales team's important indicators and interactive reports that can be shared across departments using a BI tool. The marketing team would be able to identify which campaigns are generating sales, while the operations team would be able to prepare for and estimate product demand. Additionally, depending on sales activity, management would be able to execute more precise business decisions. Accurate Sales Forecasts Companies that foresee future trends and performance have a competitive edge since it allows you to be agile. A BI solution unifies and simplifies all of your data, providing you with the most precise and up-to-date information. Having access to all of your previous sales trends in one location makes it simpler to correctly forecast future income and sales. By removing the difficulties of collecting past and current data in one place, your team can create more realistic goals, which can be tough if your sales performance is dependent on factors such as the month, client segments, and so on. Improves Customer Retention It is a known fact that offering and selling your services or goods to an existing customer is cheaper than acquiring new customers, who might cost up to seven times more. A BI system can assist a company's sales team in understanding what drives current customers and what they purchase, tracking demand patterns, and recognizing chances to cross-sell, which can then be utilized to create sales efforts. Closing Lines Utilizing business intelligence effectively can assist your business in improving customer retention, increasing income from sales efforts, and keeping your sales analytics up-to-date. As sales drive company development, a business intelligence solution like Power BI might be one of the most important investments you make. Business intelligence, whether for a major corporation or a small business, can provide your sales force with the competitive advantage it needs to stay ahead.

Read More
Big Data Management

Why Adaptive AI Can Overtake Traditional AI

Article | July 12, 2022

With the ever-changing technology world, company demands and results are no longer the norm. Businesses in a variety of sectors are using artificial intelligence (AI) technologies to solve complicated business challenges, build intelligent and self-sustaining solutions, and, ultimately, remain competitive at all times. To that aim, ongoing attempts are being made to reinvent AI systems in order to do more with less. Adaptive AI is a significant step in that direction. It has the potential to outperform standard machine learning (ML) models in the near future because of its ability to enable organizations to get greater results while spending less time, effort, and resources. The capacity of adaptive AI to enable enterprises to achieve greater outcomes while investing less time, effort, and assets is why it can overtake traditional AI models. Why Adaptive AI Overtakes Traditional AI Robust, Efficient and Agile Robustness, efficiency, and agility are the three basic pillars of Adaptive AI. The ability to achieve great algorithmic accuracy is referred to as robustness. The capacity to achieve reduced resource utilization is referred to as efficiency (for example, computer, memory, and power). Agility manages the ability to change operational circumstances in response to changing demands. Together, these three Adaptive AI principles provide the groundwork for super-capable AI inference for edge devices. Data-Informed Predictions A single pipeline is used by the adaptive learning approach. With this method, you can use a continually advanced learning approach that maintains the framework up-to-date and encourages it to achieve high levels of performance. The Adaptive Learning method examines and learns new changes made to the information and produces values, as well as their associated attributes. Moreover, it benefits from events that can modify market behavior in real-time and, as a result, maintains its accuracy consistently. Adaptive AI recognizes information from the operational environment and uses it to produce data-informed predictions. Closing Lines Adaptive AI will be utilized to meet changing AI computing requirements. Operational effectiveness depends on algorithmic performance and available computer resources. Edge AI frameworks that can change their computing demands effectively reduce compute and memory requirements. Adaptive AI is robust in CSPs' dynamic software environments, where inputs and outputs alter with each framework revamp. It can assist with network operations, marketing, customer service, IoT, security, and customer experience.

Read More
MORE ARTICLES

Spotlight

Silver Touch Technologies Ltd

IT company active in Software Outsourcing, IT Consulting, System Integration. Having global presence for service delivery in USA, UK and France. Work with global brand leaders like SAP, Oracle, Microsoft, IBM to provide IT solution and integration services. Unique Software outsourcing model called - Global Application Delivery Model (GADM) to serve client across the world.

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Airbyte Racks Up Awards from InfoWorld, BigDATAwire, Built In; Builds Largest and Fastest-Growing User Community

Airbyte | January 30, 2024

Airbyte, creators of the leading open-source data movement infrastructure, today announced a series of accomplishments and awards reinforcing its standing as the largest and fastest-growing data movement community. With a focus on innovation, community engagement, and performance enhancement, Airbyte continues to revolutionize the way data is handled and processed across industries. “Airbyte proudly stands as the front-runner in the data movement landscape with the largest community of more than 5,000 daily users and over 125,000 deployments, with monthly data synchronizations of over 2 petabytes,” said Michel Tricot, co-founder and CEO, Airbyte. “This unparalleled growth is a testament to Airbyte's widespread adoption by users and the trust placed in its capabilities.” The Airbyte community has more than 800 code contributors and 12,000 stars on GitHub. Recently, the company held its second annual virtual conference called move(data), which attracted over 5,000 attendees. Airbyte was named an InfoWorld Technology of the Year Award finalist: Data Management – Integration (in October) for cutting-edge products that are changing how IT organizations work and how companies do business. And, at the start of this year, was named to the Built In 2024 Best Places To Work Award in San Francisco – Best Startups to Work For, recognizing the company's commitment to fostering a positive work environment, remote and flexible work opportunities, and programs for diversity, equity, and inclusion. Today, the company received the BigDATAwire Readers/Editors Choice Award – Big Data and AI Startup, which recognizes companies and products that have made a difference. Other key milestones in 2023 include the following. Availability of more than 350 data connectors, making Airbyte the platform with the most connectors in the industry. The company aims to increase that to 500 high-quality connectors supported by the end of this year. More than 2,000 custom connectors were created with the Airbyte No-Code Connector Builder, which enables data connectors to be made in minutes. Significant performance improvement with database replication speed increased by 10 times to support larger datasets. Added support for five vector databases, in addition to unstructured data sources, as the first company to build a bridge between data movement platforms and artificial intelligence (AI). Looking ahead, Airbyte will introduce data lakehouse destinations, as well as a new Publish feature to push data to API destinations. About Airbyte Airbyte is the open-source data movement infrastructure leader running in the safety of your cloud and syncing data from applications, APIs, and databases to data warehouses, lakes, and other destinations. Airbyte offers four products: Airbyte Open Source, Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte. Airbyte was co-founded by Michel Tricot (former director of engineering and head of integrations at Liveramp and RideOS) and John Lafleur (serial entrepreneur of dev tools and B2B). The company is headquartered in San Francisco with a distributed team around the world. To learn more, visit airbyte.com.

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The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

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data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

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Airbyte Racks Up Awards from InfoWorld, BigDATAwire, Built In; Builds Largest and Fastest-Growing User Community

Airbyte | January 30, 2024

Airbyte, creators of the leading open-source data movement infrastructure, today announced a series of accomplishments and awards reinforcing its standing as the largest and fastest-growing data movement community. With a focus on innovation, community engagement, and performance enhancement, Airbyte continues to revolutionize the way data is handled and processed across industries. “Airbyte proudly stands as the front-runner in the data movement landscape with the largest community of more than 5,000 daily users and over 125,000 deployments, with monthly data synchronizations of over 2 petabytes,” said Michel Tricot, co-founder and CEO, Airbyte. “This unparalleled growth is a testament to Airbyte's widespread adoption by users and the trust placed in its capabilities.” The Airbyte community has more than 800 code contributors and 12,000 stars on GitHub. Recently, the company held its second annual virtual conference called move(data), which attracted over 5,000 attendees. Airbyte was named an InfoWorld Technology of the Year Award finalist: Data Management – Integration (in October) for cutting-edge products that are changing how IT organizations work and how companies do business. And, at the start of this year, was named to the Built In 2024 Best Places To Work Award in San Francisco – Best Startups to Work For, recognizing the company's commitment to fostering a positive work environment, remote and flexible work opportunities, and programs for diversity, equity, and inclusion. Today, the company received the BigDATAwire Readers/Editors Choice Award – Big Data and AI Startup, which recognizes companies and products that have made a difference. Other key milestones in 2023 include the following. Availability of more than 350 data connectors, making Airbyte the platform with the most connectors in the industry. The company aims to increase that to 500 high-quality connectors supported by the end of this year. More than 2,000 custom connectors were created with the Airbyte No-Code Connector Builder, which enables data connectors to be made in minutes. Significant performance improvement with database replication speed increased by 10 times to support larger datasets. Added support for five vector databases, in addition to unstructured data sources, as the first company to build a bridge between data movement platforms and artificial intelligence (AI). Looking ahead, Airbyte will introduce data lakehouse destinations, as well as a new Publish feature to push data to API destinations. About Airbyte Airbyte is the open-source data movement infrastructure leader running in the safety of your cloud and syncing data from applications, APIs, and databases to data warehouses, lakes, and other destinations. Airbyte offers four products: Airbyte Open Source, Airbyte Self-Managed, Airbyte Cloud, and Powered by Airbyte. Airbyte was co-founded by Michel Tricot (former director of engineering and head of integrations at Liveramp and RideOS) and John Lafleur (serial entrepreneur of dev tools and B2B). The company is headquartered in San Francisco with a distributed team around the world. To learn more, visit airbyte.com.

Read More

Big Data Management

The Modern Data Company Recognized in Gartner's Magic Quadrant for Data Integration

The Modern Data Company | January 23, 2024

The Modern Data Company, recognized for its expertise in developing and managing advanced data products, is delighted to announce its distinction as an honorable mention in Gartner's 'Magic Quadrant for Data Integration Tools,' powered by our leading product, DataOS. “This accolade underscores our commitment to productizing data and revolutionizing data management technologies. Our focus extends beyond traditional data management, guiding companies on their journey to effectively utilize data, realize tangible ROI on their data investments, and harness advanced technologies such as AI, ML, and Large Language Models (LLMs). This recognition is a testament to Modern Data’s alignment with the latest industry trends and our dedication to setting new standards in data integration and utilization.” – Srujan Akula, CEO of The Modern Data Company The inclusion in the Gartner report highlights The Modern Data Company's pivotal role in shaping the future of data integration. Our innovative approach, embodied in DataOS, enables businesses to navigate the complexities of data management, transforming data into a strategic asset. By simplifying data access and integration, we empower organizations to unlock the full potential of their data, driving insights and innovation without disruption. "Modern Data's recognition as an Honorable Mention in the Gartner MQ for Data Integration is a testament to the transformative impact their solutions have on businesses like ours. DataOS has been pivotal in allowing us to integrate multiple data sources, enabling our teams to have access to the data needed to make data driven decisions." – Emma Spight, SVP Technology, MIND 24-7 The Modern Data Company simplifies how organizations manage, access, and interact with data using its DataOS (data operating system) that unifies data silos, at scale. It provides ontology support, graph modeling, and a virtual data tier (e.g. a customer 360 model). From a technical point of view, it closes the gap from conceptual to physical data model. Users can define conceptually what they want and its software traverses and integrates data. DataOS provides a structured, repeatable approach to data integration that enhances agility and ensures high-quality outputs. This shift from traditional pipeline management to data products allows for more efficient data operations, as each 'product' is designed with a specific purpose and standardized interfaces, ensuring consistency across different uses and applications. With DataOS, businesses can expect a transformative impact on their data strategies, marked by increased efficiency and a robust framework for handling complex data ecosystems, allowing for more and faster iterations of conceptual models. About The Modern Data Company The Modern Data Company, with its flagship product DataOS, revolutionizes the creation of data products. DataOS® is engineered to build and manage comprehensive data products to foster data mesh adoption, propelling organizations towards a data-driven future. DataOS directly addresses key AI/ML and LLM challenges: ensuring quality data, scaling computational resources, and integrating seamlessly into business processes. In our commitment to provide open systems, we have created an open data developer platform specification that is gaining wide industry support.

Read More

Big Data Management

data.world Integrates with Snowflake Data Quality Metrics to Bolster Data Trust

data.world | January 24, 2024

data.world, the data catalog platform company, today announced an integration with Snowflake, the Data Cloud company, that brings new data quality metrics and measurement capabilities to enterprises. The data.world Snowflake Collector now empowers enterprise data teams to measure data quality across their organization on-demand, unifying data quality and analytics. Customers can now achieve greater trust in their data quality and downstream analytics to support mission-critical applications, confident data-driven decision-making, and AI initiatives. Data quality remains one of the top concerns for chief data officers and a critical barrier to creating a data-driven culture. Traditionally, data quality assurance has relied on manual oversight – a process that’s tedious and fraught with inefficacy. The data.world Data Catalog Platform now delivers Snowflake data quality metrics directly to customers, streamlining quality assurance timelines and accelerating data-first initiatives. Data consumers can access contextual information in the catalog or directly within tools such as Tableau and PowerBI via Hoots – data.world’s embedded trust badges – that broadcast data health status and catalog context, bolstering transparency and trust. Additionally, teams can link certification and DataOps workflows to Snowflake's data quality metrics to automate manual workflows and quality alerts. Backed by a knowledge graph architecture, data.world provides greater insight into data quality scores via intelligence on data provenance, usage, and context – all of which support DataOps and governance workflows. “Data trust is increasingly crucial to every facet of business and data teams are struggling to verify the quality of their data, facing increased scrutiny from developers and decision-makers alike on the downstream impacts of their work, including analytics – and soon enough, AI applications,” said Jeff Hollan, Director, Product Management at Snowflake. “Our collaboration with data.world enables data teams and decision-makers to verify and trust their data’s quality to use in mission-critical applications and analytics across their business.” “High-quality data has always been a priority among enterprise data teams and decision-makers. As enterprise AI ambitions grow, the number one priority is ensuring the data powering generative AI is clean, consistent, and contextual,” said Bryon Jacob, CTO at data.world. “Alongside Snowflake, we’re taking steps to ensure data scientists, analysts, and leaders can confidently feed AI and analytics applications data that delivers high-quality insights, and supports the type of decision-making that drives their business forward.” The integration builds on the robust collaboration between data.world and Snowflake. Most recently, the companies announced an exclusive offering for joint customers, streamlining adoption timelines and offering a new attractive price point. The data.world's knowledge graph-powered data catalog already offers unique benefits for Snowflake customers, including support for Snowpark. This offering is now available to all data.world enterprise customers using the Snowflake Collector, as well as customers taking advantage of the Snowflake-only offering. To learn more about the data quality integration or the data.world data catalog platform, visit data.world. About data.world data.world is the data catalog platform built for your AI future. Its cloud-native SaaS (software-as-a-service) platform combines a consumer-grade user experience with a powerful Knowledge Graph to deliver enhanced data discovery, agile data governance, and actionable insights. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. Our company has 76 patents and has been named one of Austin’s Best Places to Work seven years in a row.

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