Data Virtualization: A Dive into the Virtual Data Lake

Aashish Yadav | August 18, 2022 | 889 views | Read Time : 02:50 min

Data Virtualization: A Dive into the Virtual Data Lake

No matter if you own a retail business, a financial services company, or an online advertising business, data is the most essential resource for contemporary businesses. Businesses are becoming more aware of the significance of their data for business analytics, machine learning, and artificial intelligence across all industries.


Smart companies are investing in innovative approaches to derive value from their data, with the goals of gaining a deeper understanding of the requirements and actions of their customers, developing more personalized goods and services, and making strategic choices that will provide them with a competitive advantage in the years to come.

Business data warehouses have been utilized for all kinds of business analytics for many decades, and there is a rich ecosystem that revolves around SQL and relational databases. Now, a competitor has entered the picture.

Data lakes were developed for the purpose of storing large amounts of data to be used in the training of AI models and predictive analytics.

For most businesses, a data lake is an essential component of any digital transformation strategy. However, getting data ready and accessible for creating insights in a controllable manner remains one of the most complicated, expensive, and time-consuming procedures. While data lakes have been around for a long time, new tools and technologies are emerging, and a new set of capabilities are being introduced to data lakes to make them more cost-effective and more widely used.


Why Should Businesses Opt for Virtual Data Lakes and Data Virtualization?

Data virtualization provides a novel approach to data lakes; modern enterprises have begun to use logical data lake architecture, which is a blended method based on a physical data lake but includes a virtual data layer to create a virtual data lake. Data virtualization combines data from several sources, locations, and formats without requiring replication. In a process that gives many applications and users unified data services, a single "virtual" data layer is created. There are many reasons and benefits for adding a virtual data lake and data virtualization, but we will have a look at the top three reasons that will benefit your business.

Reduced Infrastructure Costs

Database virtualization can save you money by eliminating the need for additional servers, operating systems, electricity, application licensing, network switches, tools, and storage.


Lower Labor Costs

Database virtualization makes the work of a database IT administrator considerably easier by simplifying the backup process and enabling them to handle several databases at once.


Data Quality

Marketers are nervous about the quality and accuracy of the data that they have. According to Singular, in 2019, 13% responded that accuracy was their top concern. And 12% reported having too much data. Database virtualization improves data quality by eliminating replication.


Virtual Data Lake and Marketing Leaders

Customer data is both challenging as well as an opportunity for marketers. If your company depends on data-driven marketing on any scale and expects to retain a competitive edge, there is no other option: it is time to invest in a virtual data lake. In the omnichannel era, identity resolution is critical to consumer data management. Without it, business marketers would be unable to develop compelling customer experiences.

Marketers could be wondering, "A data what?" Consider data lakes in this manner: They provide marketers with important information about the consumer journey as well as immediate responses about marketing performance across various channels and platforms. Most marketers lack insight into performance because they lack the time and technology to filter through all of the sources of that information. A virtual data lake is one solution.

Marketers can reliably answer basic questions like, "How are customers engaging with our goods and services, and where is that occurring in the customer journey?" using a data lake. "At what point do our conversion rates begin to decline?" The capacity to detect and solve these sorts of errors at scale and speed—with precise attribution and without double-counting—is invaluable.

Marketers can also use data lakes to develop appropriate standards and get background knowledge of activity performance. This provides insight into marketing ROI and acts as a resource for any future marketing initiatives and activities.


Empowering Customer Data Platform Using Data Virtualization

Businesses are concentrating more than ever on their online operations, which means they are spending more on digital transformation. This involves concentrating on "The Customer," their requirements and insights. Customers have a choice; switching is simple, and customer loyalty is inexpensive, making it even more crucial to know your customer and satisfy their requirements.

Data virtualization implies that the customer data platform (CDP) serves as a single data layer that is abstracted from the data source's data format or schemas. The CDP offers just the data selected by the user with no bulk data duplication. This eliminates the need for a data integrator to put up a predetermined schema or fixed field mappings for various event types.


Retail Businesses are Leveraging Data Virtualization

Retailers have been servicing an increasingly unpredictable customer base over the last two decades. They have the ability to do research, check ratings, compare notes among their personal and professional networks, and switch brands. They now expect to connect with retail businesses in the same way that they interact with social networks.

To accomplish so, both established as well as modern retail businesses must use hybrid strategies that combine physical and virtual businesses. In order to achieve this, retail businesses are taking the help of data virtualization to provide seamless experiences across online and in-store environments.


How Does Data Virtualization Help in the Elimination of Data Silos?

To address these data-silo challenges, several businesses are adopting a much more advanced data integration strategy: data virtualization. In reality, data virtualization and data lakes overlap in many aspects. Both architectures start with the assumption that all data should be accessible to end users. Broad access to big data volumes is employed in both systems to better enable BI and analytics as well as other emerging trends like artificial intelligence and machine learning.

Data Virtualization can address a number of big data pain points with features such as query pushdown, caching, and query optimization. Data virtualization enables businesses to access data from various sources such as data warehouses, NoSQL databases, and data lakes without requiring physical data transportation thanks to a virtual layer that covers the complexities of source data from the end user.

A couple of use cases where data virtualization can eliminate data silos are:


Agile Business Intelligence

Legacy BI solutions are now unable to meet the rising enterprise BI requirements. Businesses now need to compete more aggressively. As a result, they must improve the agility of their processes.

Data virtualization can improve system agility by integrating data on-demand. Moreover, it offers uniform access to data in a unified layer that can be merged, processed, and cleaned. Businesses may also employ data virtualization to build consistent BI reports for analysis with reduced data structures and instantly provide insights to key decision-makers.


Virtual Operational Data Store

The Virtual Operational Data Store (VODS) is another noteworthy use of data virtualization. Users can utilize VODS to execute additional operations on the data analyzed by data virtualization, like monitoring, reporting, and control. GPS applications are a perfect example of VODS. Travelers can utilize these applications to get the shortest route to a certain location.

A VODS takes data from a variety of data repositories and generates reports on the fly. So, the traveler gets information from a variety of sources without having to worry about which one is the main source.


Closing Lines

Data warehouses and virtual data lakes are both effective methods for controlling huge amounts of data and advancing to advanced ML analytics. Virtual data lakes are a relatively new technique for storing massive amounts of data on commercial clouds like Amazon S3 and Azure Blob.

While dealing with ML workloads, the capacity of a virtual data lake and data virtualization to harness more data from diverse sources in much less time is what makes it a preferable solution. It not only allows users to cooperate and analyze data in new ways, but it also accelerates decision-making. When you require business-friendly and well-engineered data displays for your customers, it makes a strong business case. Through data virtualization, IT can swiftly deploy and repeat a new data set as client needs change.

When you need real-time information or want to federate data from numerous sources, data virtualization can let you connect to it rapidly and provide it fresh each time.


Frequently Asked Questions

What Exactly Is a “Virtual Data Lake?”

A virtual data lake is connected to or disconnected from data sources as required by the applications that are using it. It stores data summaries in the sources such that applications can explore the data as if it were a single data collection and obtain entire items as required.


What Is the Difference Between a Data Hub and a Data Lake?

Data Lakes and Data Hubs (Datahub) are two types of storage systems. A data lake is a collection of raw data that is primarily unstructured. On the other hand, a data hub, is made up of a central storage system whose data is distributed throughout several areas in a star architecture.


Does Data Virtualization Store Data?

It is critical to understand that data virtualization doesn't at all replicate data from source systems; rather, it saves metadata and integration logic for viewing.

Spotlight

Grockit

Grockit makes learning products that help people optimize their study time, improve their test scores and study together. Grockit provides its global network of learners an experience informed by educational research and data analysis…

OTHER ARTICLES
BIG DATA MANAGEMENT

How is Data Virtualization Shifting the Tailwind in Data Management?

Article | June 24, 2022

Over the past couple of years, a significant rise in the trend of digitalization has been witnessed across almost all industries, resulting in the creation of large volumes of data. In addition, an unprecedented proliferation of applications and the rise in the use of social media, cloud and mobile computing, the Internet of Things, and others have created the need for collecting, combining, and curating massive amounts of data. As the importance of data continues to grow across businesses, companies aim to collect data from the web, social media, AI-powered devices, and other sources in different formats, making it trickier for them to manage this unstructured data. Hence, smarter companies are investing in innovative solutions, such as data virtualization, to access and modify data stored across siloed, disparate systems through a unified view. This helps them bridge critical decision-making data together, fuel analytics, and make strategic and well-informed decisions. Why is Data Virtualization Emerging as A New Frontier in Data Management? In the current competitive corporate world, where data needs are increasing at the same rate as the volume of data companies hold, it is becoming essential to manage and harness data effectively. As enterprises focus on accumulating multiple types of data, the effort of managing it has outgrown the capacity of traditional data integration tools, such as data warehouse software and Extract Transform Load (ETL) systems. With the growing need for more effective data integration solutions, high-speed information sharing, and non-stop data transmission, advanced tools such as data virtualization are gaining massive popularity among corporate firms and other IT infrastructures. Data virtualization empowers organizations to accumulate and integrate data from multiple channels, locations, sources, and formats to create a unified stream of data without any redundancy or overlap, resulting in faster integration speeds and enhanced decision-making. What are the key features that make data virtualization a new frontier in data management? Let's see: Modernize Information Infrastructure With the ability to hide the underlying systems, data virtualization allows companies to replace their old infrastructure with cutting-edge cloud applications without affecting day-to-day business operations. Enhance Data Protection Data virtualization enables CxOs to identify and isolate vital source systems from users and applications, which assists organizations in preventing the latter from making unintended changes to the data, as well as allowing them to enforce data governance and security. Deliver Information Faster and Cheaper Data replication takes time and costs money; the "zero replication" method used by data virtualization allows businesses to obtain up-to-the-minute information without having to invest in additional storage space, thereby saving on the operation cost. Increase Business Productivity By delivering data in real time, the integration of data virtualization empowers businesses to access the most recent data during regular business operations. In addition, it enhances the utilization of servers and storage resources and allows data engineering teams to do more in less time, thereby increasing productivity. Use Fewer Development Resources Data virtualization lowers the need for human coding, allowing developers to focus on the faster delivery of information at scale. With its simplified view-based methodology, data virtualization also enables CxOs to reduce development resources by around one-fourth. Data Virtualization: The Future Ahead With the growing significance of data across enterprises and increasing data volume, variety, complexity, compliance requirements, and others, every organization is looking for well-governed, consistent, and secure data that is easy to access and use. As data virtualization unifies and integrates the data from different systems, providing new ways to access, manage, and deliver data without replicating it, more and more organizations are investing in data virtualization software and solutions and driving greater business value from their data.

Read More
BUSINESS INTELLIGENCE

How Artificial Intelligence Is Transforming Businesses

Article | August 4, 2022

Whilst there are many people that associate AI with sci-fi novels and films, its reputation as an antagonist to fictional dystopic worlds is now becoming a thing of the past, as the technology becomes more and more integrated into our everyday lives.AI technologies have become increasingly more present in our daily lives, not just with Alexa’s in the home, but also throughout businesses everywhere, disrupting a variety of different industries with often tremendous results. The technology has helped to streamline even the most mundane of tasks whilst having a breath-taking impact on a company’s efficiency and productivity.However, AI has not only transformed administrative processes and freed up more time for companies, it has also contributed to some ground-breaking moments in business, being a must-have for many in order to keep up with the competition.

Read More
BIG DATA MANAGEMENT

DRIVING DIGITAL TRANSFORMATION WITH RPA, ML AND WORKFLOW AUTOMATION

Article | July 15, 2022

The latest pace of advancements in technology paves way for businesses to pay attention to digital strategy in order to drive effective digital transformation. Digital strategy focuses on leveraging technology to enhance business performance, specifying the direction where organizations can create new competitive advantages with it. Despite a lot of buzz around its advancement, digital transformation initiatives in most businesses are still in its infancy.Organizations that have successfully implemented and are effectively navigating their way towards digital transformation have seen that deploying a low-code workflow automation platform makes them more efficient.

Read More

AI and Predictive Analytics: Myth, Math, or Magic

Article | February 10, 2020

We are a species invested in predicting the future as if our lives depended on it. Indeed, good predictions of where wolves might lurk were once a matter of survival. Even as civilization made us physically safer, prediction has remained a mainstay of culture, from the haruspices of ancient Rome inspecting animal entrails to business analysts dissecting a wealth of transactions to foretell future sales. With these caveats in mind, I predict that in 2020 (and the decade ahead) we will struggle if we unquestioningly adopt artificial intelligence (AI) in predictive analytics, founded on an unjustified overconfidence in the almost mythical power of AI's mathematical foundations. This is another form of the disease of technochauvinism I discussed in a previous article.

Read More

Spotlight

Grockit

Grockit makes learning products that help people optimize their study time, improve their test scores and study together. Grockit provides its global network of learners an experience informed by educational research and data analysis…

Related News

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Clarivate Expands Real World Data and Analytics Solutions with Addition of U.S. Specialty Pharmacy Data

Clarivate | December 06, 2022

Clarivate Plc, a global leader in providing trusted information and insights to accelerate the pace of innovation, today announced the inclusion of linked specialty pharmacy claims data within real world data solutions. The new U.S. dataset will expand the real world data and analytics offerings from Clarivate. Researchers can access an in-depth view of high-cost medications and valuable insights into the patient's treatment journey in chronic, complex and rare diseases, such as rheumatoid arthritis (e.g., Humira, Enbrel), inflammatory conditions (e.g., Dupixent, Otezla), and cancer (e.g., Xgeva, Xeloda). Specialty drugs cover at least 20% of the market for chronic, complex and rare diseases. However, conventional claims data warehouses rarely include these high-cost medications, which limits the research potential of numerous diseases. Specialty pharmacy data enables life sciences professionals to: Track specialty drug uptake and understand market dynamics (market and launch analytics) Build brand-level patient profiles (brand analytics, patient journey) Measure non/adherence and switching patterns (persistency and adherence analysis) Target and appropriately engage prescribers and providers (commercial targeting) Researchers can leverage this real-world dataset to make evidence-based decisions -- developing successful strategies, optimizing commercial resources, and defining the right activities and messaging to improve patient outcomes. "Clarivate is committed to supporting customers across the drug, device and diagnostic lifecycle with timely, fit-for-purpose real world data solutions. The addition of integrated, high-capture specialty pharmacy data to the Clarivate portfolio further expands the set of questions that can be answered in the data by reducing fragmentation and bias and providing a more holistic view of the patient." Matt McKinley, VP, Head of Real World Data & Analytics The specialty pharmacy data covers over 500 specialty drugs spanning diverse therapeutic areas. The data enables a holistic analysis of complex clinical profiles reducing the need for additional data mapping or processing. The unique data and insights are updated weekly, allowing users to track changes in clinical pathways, product uptake and market dynamics. About Clarivate Clarivate™ is a global leader in providing solutions to accelerate the pace of innovation. Our bold mission is to help customers solve some of the world's most complex problems by providing actionable information and insights that reduce the time from new ideas to life-changing inventions in the areas of Academia & Government, Life Sciences & Healthcare, Professional Services and Consumer Goods, Manufacturing & technology. We help customers discover, protect and commercialize their inventions using our trusted subscription and technology-based solutions coupled with deep domain expertise.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Foursquare to Power Geospatial Data Visualization in Amazon SageMaker

Foursquare | December 06, 2022

Foursquare, the leading independent location technology company, exclusively powers data visualization for the new Amazon SageMaker geospatial capabilities announced last week at Amazon Web Services (AWS) re:Invent 2022. Foursquare Studio can visualize geospatial data at a massive scale with ease, enabling data scientists to explore geospatial data interactively and seamlessly on a map as they build, train, and deploy ML models on Amazon SageMaker. The world's most innovative companies rely on geospatial data to make critical business decisions. Many of them, including Uber, Redfin and DoorDash, already work with Foursquare to enrich their business processes with location data and analytics tools. As more and more enterprises realize the opportunity for geospatial data to improve their decisions, they are looking for simpler ways to extract insights using cutting edge ML models. Before today, data scientists and ML engineers had to build and assemble a complicated chain of data sets and ML tools to extract insights from geospatial data, slowing down their pace of innovation. Using Foursquare Studio, data scientists and ML engineers can explore massive geospatial datasets interactively. With Foursquare Studio in Amazon SageMaker, customers can extract geospatial features of predictive value, such as identifying the most frequently traversed areas of a city or detecting traffic patterns after an event, to make predictions. Utilizing these geospatial features, they can also build ML models that enable business analysts to make smarter and faster decisions, such as choosing where to locate their next store or estimate the value of a property based on the characteristics of its neighborhood. “Foursquare continues to invest in location technologies that serve enterprises as well as consumers. “Having worked with AWS to build Foursquare Studio in Amazon SageMaker, we are excited to see customers use the new geospatial capabilities to generate meaningful insights. Many businesses are already using Foursquare data and tools along with AWS analytics and machine learning services. We look forward to helping many more enterprises unlock the potential of geospatial data with Foursquare Studio in Amazon SageMaker.” Ankit Patel, SVP of Engineering at Foursquare About Foursquare Foursquare is the leading independent location technology company, dedicated to helping businesses make smarter decisions and developers create more engaging user experiences. A pioneer of the geolocation space, Foursquare’s geospatial capabilities are used by the world’s largest enterprises and most recognizable brands, helping them take advantage of location intelligence to create better customer experiences and smarter business outcomes.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Bright Data Launches Public Web Datasets on Snowflake Marketplace

Bright Data | December 05, 2022

Bright Data announced today its partnership with Snowflake, the Data Cloud company, and as such, the launch of its Datasets on Snowflake Marketplace. The new solution will provide joint customers with ready-to-use, pre-made datasets to help them acquire the web data they need to make critical decisions and address challenging business questions across every aspect of their organization. Snowflake Marketplace, powered by Snowflake’s ground-breaking cross-cloud technology, Snowgrid, allows companies to get direct access to raw data products and leverage data, data services and applications quickly, securely, and cost-effectively. Snowflake Marketplace simplifies discovery, access, and the commercialization of data products enabling companies to unlock entirely new revenue streams and extended insights across the Data Cloud. The new solution will forward customers a unique ability to search, discover, filter through, and obtain large and complete datasets procured by the Bright Data team — containing millions of web data points from public e-Commerce & shopping, travel & tourism, as well as business information websites, refreshed at periodic intervals — to receive comprehensive coverage of entire target websites, delivered within a structured format. Furthermore, customers from across multiple market sectors will be able to request custom-made datasets and subsets of pre-made datasets to create a focus on the specific set of information that provides value to their organizations. Customers will be able to enjoy varying possibilities for data enrichment that can produce additional information on top of the web data already collected from public websites and add further value to the requested dataset. “Both tailored and pre-made datasets are becoming significantly more attractive for organizations of all sizes. “The smartest players are using a combination of both offerings, whether it is specifically tailored public datasets or ready-made to address their most essential questions and provide the immediate answers that drive their organizations further.” Bright Data CEO Or Lenchner “Bringing Bright Data’s datasets to Snowflake Marketplace will enable our joint customers to pursue innovation within their web data collection efforts,” said Kieran Kennedy, Head of Snowflake Marketplace. “As Snowflake continues to empower organizations to mobilize their data, partners like Bright Data give our customers greater flexibility around how they acquire and collect web data at scale.” About Bright Data Bright Data is the industry-leading web data platform. Fortune 500 companies, academic institutions, and small businesses rely on Bright Data’s solutions to retrieve web data in the most efficient, reliable, and flexible way so they can research, monitor, and analyze it to make better and faster decisions that directly impact their business success.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Clarivate Expands Real World Data and Analytics Solutions with Addition of U.S. Specialty Pharmacy Data

Clarivate | December 06, 2022

Clarivate Plc, a global leader in providing trusted information and insights to accelerate the pace of innovation, today announced the inclusion of linked specialty pharmacy claims data within real world data solutions. The new U.S. dataset will expand the real world data and analytics offerings from Clarivate. Researchers can access an in-depth view of high-cost medications and valuable insights into the patient's treatment journey in chronic, complex and rare diseases, such as rheumatoid arthritis (e.g., Humira, Enbrel), inflammatory conditions (e.g., Dupixent, Otezla), and cancer (e.g., Xgeva, Xeloda). Specialty drugs cover at least 20% of the market for chronic, complex and rare diseases. However, conventional claims data warehouses rarely include these high-cost medications, which limits the research potential of numerous diseases. Specialty pharmacy data enables life sciences professionals to: Track specialty drug uptake and understand market dynamics (market and launch analytics) Build brand-level patient profiles (brand analytics, patient journey) Measure non/adherence and switching patterns (persistency and adherence analysis) Target and appropriately engage prescribers and providers (commercial targeting) Researchers can leverage this real-world dataset to make evidence-based decisions -- developing successful strategies, optimizing commercial resources, and defining the right activities and messaging to improve patient outcomes. "Clarivate is committed to supporting customers across the drug, device and diagnostic lifecycle with timely, fit-for-purpose real world data solutions. The addition of integrated, high-capture specialty pharmacy data to the Clarivate portfolio further expands the set of questions that can be answered in the data by reducing fragmentation and bias and providing a more holistic view of the patient." Matt McKinley, VP, Head of Real World Data & Analytics The specialty pharmacy data covers over 500 specialty drugs spanning diverse therapeutic areas. The data enables a holistic analysis of complex clinical profiles reducing the need for additional data mapping or processing. The unique data and insights are updated weekly, allowing users to track changes in clinical pathways, product uptake and market dynamics. About Clarivate Clarivate™ is a global leader in providing solutions to accelerate the pace of innovation. Our bold mission is to help customers solve some of the world's most complex problems by providing actionable information and insights that reduce the time from new ideas to life-changing inventions in the areas of Academia & Government, Life Sciences & Healthcare, Professional Services and Consumer Goods, Manufacturing & technology. We help customers discover, protect and commercialize their inventions using our trusted subscription and technology-based solutions coupled with deep domain expertise.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Foursquare to Power Geospatial Data Visualization in Amazon SageMaker

Foursquare | December 06, 2022

Foursquare, the leading independent location technology company, exclusively powers data visualization for the new Amazon SageMaker geospatial capabilities announced last week at Amazon Web Services (AWS) re:Invent 2022. Foursquare Studio can visualize geospatial data at a massive scale with ease, enabling data scientists to explore geospatial data interactively and seamlessly on a map as they build, train, and deploy ML models on Amazon SageMaker. The world's most innovative companies rely on geospatial data to make critical business decisions. Many of them, including Uber, Redfin and DoorDash, already work with Foursquare to enrich their business processes with location data and analytics tools. As more and more enterprises realize the opportunity for geospatial data to improve their decisions, they are looking for simpler ways to extract insights using cutting edge ML models. Before today, data scientists and ML engineers had to build and assemble a complicated chain of data sets and ML tools to extract insights from geospatial data, slowing down their pace of innovation. Using Foursquare Studio, data scientists and ML engineers can explore massive geospatial datasets interactively. With Foursquare Studio in Amazon SageMaker, customers can extract geospatial features of predictive value, such as identifying the most frequently traversed areas of a city or detecting traffic patterns after an event, to make predictions. Utilizing these geospatial features, they can also build ML models that enable business analysts to make smarter and faster decisions, such as choosing where to locate their next store or estimate the value of a property based on the characteristics of its neighborhood. “Foursquare continues to invest in location technologies that serve enterprises as well as consumers. “Having worked with AWS to build Foursquare Studio in Amazon SageMaker, we are excited to see customers use the new geospatial capabilities to generate meaningful insights. Many businesses are already using Foursquare data and tools along with AWS analytics and machine learning services. We look forward to helping many more enterprises unlock the potential of geospatial data with Foursquare Studio in Amazon SageMaker.” Ankit Patel, SVP of Engineering at Foursquare About Foursquare Foursquare is the leading independent location technology company, dedicated to helping businesses make smarter decisions and developers create more engaging user experiences. A pioneer of the geolocation space, Foursquare’s geospatial capabilities are used by the world’s largest enterprises and most recognizable brands, helping them take advantage of location intelligence to create better customer experiences and smarter business outcomes.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Bright Data Launches Public Web Datasets on Snowflake Marketplace

Bright Data | December 05, 2022

Bright Data announced today its partnership with Snowflake, the Data Cloud company, and as such, the launch of its Datasets on Snowflake Marketplace. The new solution will provide joint customers with ready-to-use, pre-made datasets to help them acquire the web data they need to make critical decisions and address challenging business questions across every aspect of their organization. Snowflake Marketplace, powered by Snowflake’s ground-breaking cross-cloud technology, Snowgrid, allows companies to get direct access to raw data products and leverage data, data services and applications quickly, securely, and cost-effectively. Snowflake Marketplace simplifies discovery, access, and the commercialization of data products enabling companies to unlock entirely new revenue streams and extended insights across the Data Cloud. The new solution will forward customers a unique ability to search, discover, filter through, and obtain large and complete datasets procured by the Bright Data team — containing millions of web data points from public e-Commerce & shopping, travel & tourism, as well as business information websites, refreshed at periodic intervals — to receive comprehensive coverage of entire target websites, delivered within a structured format. Furthermore, customers from across multiple market sectors will be able to request custom-made datasets and subsets of pre-made datasets to create a focus on the specific set of information that provides value to their organizations. Customers will be able to enjoy varying possibilities for data enrichment that can produce additional information on top of the web data already collected from public websites and add further value to the requested dataset. “Both tailored and pre-made datasets are becoming significantly more attractive for organizations of all sizes. “The smartest players are using a combination of both offerings, whether it is specifically tailored public datasets or ready-made to address their most essential questions and provide the immediate answers that drive their organizations further.” Bright Data CEO Or Lenchner “Bringing Bright Data’s datasets to Snowflake Marketplace will enable our joint customers to pursue innovation within their web data collection efforts,” said Kieran Kennedy, Head of Snowflake Marketplace. “As Snowflake continues to empower organizations to mobilize their data, partners like Bright Data give our customers greater flexibility around how they acquire and collect web data at scale.” About Bright Data Bright Data is the industry-leading web data platform. Fortune 500 companies, academic institutions, and small businesses rely on Bright Data’s solutions to retrieve web data in the most efficient, reliable, and flexible way so they can research, monitor, and analyze it to make better and faster decisions that directly impact their business success.

Read More

Events