The Many Faces of Metadata Management

March 20, 2019 | 27 views

Metadata is “data about the data,” and managing it correctly can improve data transparency and accessibility while helping organizations track and understand data lineage and improve data governance. Good metadata also gives users more confidence in BI reports and analytics. Unfortunately, TDWI research finds that most organizations still acquire and manage metadata manually and haphazardly using methods that are slow and do not scale. In addition, there is confusion about the differences between metadata repositories, data catalogs, and business glossaries. The good news is that understanding and applying better metadata management to your organization’s data management and integration practices can help with BI reporting, analytics, data governance, migration, and regulatory adherence.

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GrowingData

GrowingData build value from data. As specialists in data science, data engineering, software engineering and data visualization, we deliver solutions that help organizations generate real value from data. From matching algorithms, to big data, to predictive analysis and machine learning, Growing Data can devise, design and implement a solution that generate new revenue and new capabilities for your organization. Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. At GrowingData, we have been working with “big data” for the past 10 years, from financial market data, through to hundreds of millions of transactions and terabytes of text data. We understand and have used platforms such a Red Shift, Hadoop all the way through to super computers to deliver systems that separate the signal from the noise…

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BUSINESS INTELLIGENCE

Augmented Analytics: The Next-Big Thing in Data Analytics

Article | August 4, 2022

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.

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BIG DATA MANAGEMENT

Can Blockchain Change The Game Of Data Analytics And Data Science?

Article | July 15, 2022

Blockchain has been causing ripples across major industries and verticals in the recent couple of years. We are seeing the future potential of blockchain technology that is scaling beyond just cryptocurrencies and trading. It is only natural that Blockchain is going to have a huge impact on Data Analytics, another field that has been booming and seems to continue in the same trajectory for the foreseeable future. However, very little research has been done on the implications of blockchain on Data Science or the potential of Data Science in Blockchain. While Blockchain is about validating data and data science is about predictions and patterns, they are linked together by the fact that they both use algorithms to control interactions between various data points. Blockchain in Big Data Analytics Big Data has traditionally been a very centralized method where we had to collate data from various sources and bring it together in one place. Blockchain, considering its decentralized nature can potentially allow analysis of data to happen at the origin nodes of individual sources. Also, considering that all data parsed through blockchain is validated across networks in a fool proof manner, the data integrity is ensured. This can be a game changer for analytics. With the digital age creating so many new data points and making data more accessible than ever, the need for diving into depth with advanced analytics has been realized by businesses around the world. However, the data is still not organized and it takes a very long time to bring them together to make sense of it. The other key challenge in Big Data remains data security. Centralized systems historically have been known for their vulnerability for leaks and hacks. A decentralized infrastructure can address both of the above challenges enabling data scientists to build a robust infrastructure to build a predictive data model and also giving rise to new possibilities for more real time analysis. Can Blockchain Enhance Data Science? Blockchain can address some of the key aspects of Data Science and Analytics. Data Security & Encoding: The smart contracts ensure that no transaction can be reversed or hidden. The complex mathematical algorithms that form the base of Blockchain are built to encrypt every single transaction on the ledger. Origin Tracing & Integrity: Blockchain technology is known for enabling P2P relationships. With blockchain technology, the ledgers can be transparent channels where the data flowing through it is validated and every stakeholder involved in the process is made accountable and accessible. This also enables the data to be of higher quality than what was possible with traditional methods. Summing Up Data science itself is fairly new and advancing in recent years. Blockchain Technology, as advanced as it seems, is still at what is believed to be a very nascent stage. We have been seeing an increasing interest in data being moved to the cloud and it is only a matter of time when businesses will want it to be moved to decentralized networks. On the other hand, blockchain’s network and server requirements are still not addressed and data analytics can be very heavy on the network, considering the volume of data collected for analysis. With very small volumes of data stored in blocks, we need viable solutions to make sure data analysis in blockchain is possible at scale. At Pyramidion, we have been working with clients globally on some exciting blockchain projects. These projects are being led by visionaries, who are looking to change how the world functions, for good. Being at the forefront of innovation, where we see the best minds working on new technologies, ICOs and protocols, we strongly believe it is only a matter of time before the challenges are addressed and Blockchain starts being a great asset to another rapidly growing field like Data Science and Data Analytics.

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BUSINESS STRATEGY

Maximize ROI with Marketing Analytics Technology

Article | July 22, 2022

Every business tries to improve their return on investment (ROI) every year by deploying different marketing strategies and technologies. Businesses are constantly adding new technologies to their content stack in order to enhance their efficiency and boost their revenue and growth. Data is inevitable in today's digital era, and Dan Zarrella correctly describes its role in marketing. He stated, "Marketing without data is like driving with your eyes closed." Indeed, the development of better marketing analytics tools and methodologies in recent years has provided business leaders with tremendous added decision-making power. Marketing analytics enables businesses to harness data points about their prospects and their journey through the selling process to enhance the effectiveness of their go-to-market efforts while optimizing ROI. The benefits can be experienced across teams and business segments. According to Hubspot, over 75% of marketers are reporting on how their campaigns are directly influencing revenue because of marketing analytics tools. So, let’s dive deeper and understand why marketing analytics matters. Why Does Marketing Analytics Matter? Marketing campaigns are just tossed into the world with little or no information about how your target audience responds to your marketing strategies. This happens in cases where business analytics tools are not used. Without employing marketing analytics, it can be said that a business is operating in the dark. Here are the reasons why marketing analytics matters. Quantifiable Actions Marketing analytics tools provide you with reliable matrices and insights into the varied marketing strategies that are implemented. Whenever numbers are presented, concrete data for the marketing effort is provided. For example, if you launched a content marketing campaign and have reliable data, it's easy to see that overall sales improved as a result of that marketing push. Campaign Analyses Only marketing analytics can provide a complete overview of how a marketing campaign or strategy actually performed. The data can be dug deeper to track individual messaging across a broad spectrum of outlets, making sure no approach is wasted. Plan for the Future Once you have an understanding of which marketing strategies are meeting expectations, you will be able to plan strategically for future marketing initiatives. Not only is this helpful for organizing marketing efforts, but it also makes it easier to allocate funds across boards. Maximize ROI with Marketing Analytics When marketers use marketing analytics tools, they can find patterns and signs that can be used to improve the performance of their company. This data can assist account managers to acquire new prospects, reallocate marketing expenditures to the most effective channels, and forecast future possibilities. Integration of marketing analytics software into the sales process can save time, boost revenue, and maximize ROI. Lead Prospecting Marketing analytics can enhance customer acquisition in multiple ways. Many marketers merely acquire data about website visitors and ad viewers via ad networks. They just receive basic demographic data, not tips about how to convert leads to sales. Marketing analytics tracks every prospect in your sales funnel or website in real-time. With a detailed picture of your potential customers, you can recognize qualified leads and target them with marketing. Using data insights, you can boost sales, get rid of bottlenecks, increase conversions, and find opportunities that were hidden in plain sight. Campaign Performance Monitoring Online advertising and marketing have the distinct advantage of allowing campaign managers to keep checks on ad performance in real-time. Businesses can use marketing ROI metrics like clicks, impressions, and conversions to figure out which ads work best. Real-time campaign monitoring is a valuable tool for today's marketers. Placements that are underperforming are paused or modified, while those with a great ROI could get extra ad revenue. These insights usually result in more efficient ad spending. Information from different media channels and data from online applications can be put together to learn about the prospect-to-customer journey. Demand Forecasting With suitable data at the right time, marketers gain more power. Tracking historical data is essential to identifying patterns and predicting demand. Seasonal patterns, for example, can have a significant impact on how well a campaign performs. Detailed research can indicate these factors and assist you in re-allocate or altering your marketing investment. Understanding the product or campaign performance helps to identify which items will be in high demand in the future quarter through the use of marketing analytics. Boost Sales Consumers are more knowledgeable than ever before. Reviews, social networks, blogs, etc., now influence most purchasing decisions. Marketing analytics provides valuable information. Focus on how marketing impacts sales to evaluate ROI. When to contact a potential customer, which product would have the most impact, and who is best suited to close the deal. Find sales-boosting marketing strategies. Marketing analytics can enhance revenue by: Understanding the decision-making process of a consumer. Tracking website user behavior and sales trends. Discussing your ROI strategy with the entire company, rather than just the sales or marketing teams. Summing Up For marketers, the use of marketing analytics technology is undoubtedly going to grow over time. You can boost your marketing ROI by using the best marketing analytics tools. Marketing ROI is mostly determined by how successful you are at developing and executing your company's marketing strategy. If you use the right marketing analytics, you can cut your marketing costs, make more people want your brand, and increase sales. FAQ What are the main components of marketing analytics? An effective marketing analytics strategy must have the following three capabilities: Scalability: Your approach must be able to grow and adapt to the changing requirements of the future. Sustainability: Having the appropriate team is essential to long-term sustainability. Affordability: Analytical is a sound investment, but the budget must be in sync with projected growth. What technology do most marketing analysts use? Marketing analysts can require various technologies related to: Statistical analysis software (e.g., R, SAS, SPSS, or STATA) SQL databases and database querying languages. What is digital marketing analytics? Customer behavior is translated into actionable company data through digital marketing analytics. Businesses can use digital analytics tools to learn more about what customers are doing online, why they're doing it, and how this behavior can be used in digital marketing campaigns.

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BUSINESS INTELLIGENCE

Business Intelligence VS Predictive Analytics: Key Differentiators

Article | May 18, 2022

Predictive analytics and business intelligence have become some of the most important tools for businesses because of their outstanding capabilities. Most people believe that predictive analytics is a part of business intelligence (BI), but that is not the case. If we look at the definition of business intelligence, we can argue that predictive analytics actually falls under the umbrella of BI, but that's not entirely true. While that definition is pretty much correct for both terms, if we dig down a little deeper, we will see that there are significant differences between business intelligence and predictive analytics in both practices as well as theories. Let’s drill down to understand the key differentiators between predictive analytics and business intelligence. Key Differentiators: Predictive Analytics VS BI BI seeks to answer queries like "what happens now" and "what is happening now," whereas predictive analytics tries to predict "what will happen" and provides a more practical method to assess information. Data Raw data is processed into insights for direct consumer use during the business intelligence process. With predictive analytics, unstructured data is turned into structured data that can be used to make predictions about the future. Decision Users can make decisions based on insights provided by business intelligence. Businesses can use predictive analytics to make decisions based on facts, data sets, and predictions. Purpose The objective of business intelligence tools is to equip users with information about their company's historical data performance. Predictive analytics utilizes forecasting techniques to help in the solving of complex business challenges. Methods Business intelligence uses data visualization, data mining, reporting, dashboards, OLAP, etc., with previous performance indicators. Predictive analytics predicts future occurrences and analyzes raw data patterns. Technologies Ad-hoc reporting technology, alerting technology, and other technologies are covered in business intelligence. Predictive analytics includes technologies such as predictive modeling, forecasting, etc. Use Predictive Analytics in Business Intelligence to Optimize Marketing Efforts Businesses now have a plethora of information about their customers’ and target audience's purchasing patterns and preferences, all thanks to business intelligence insights. With all of this information, predictive analytics can determine the possibility of a consumer purchasing a product, allowing businesses to target their marketing efforts on customers who are more likely to purchase their items. Businesses that employ predictive analytics and business intelligence solutions can constantly remain one step ahead of their competition. Summing Up At times, the sheer variety of tools available can be intimidating, and misinformation can sometimes hamper the selection process of technology. Business intelligence and predictive analytics are two of the most productive technologies in the market, but when combined, they can do wonders for businesses.

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Spotlight

GrowingData

GrowingData build value from data. As specialists in data science, data engineering, software engineering and data visualization, we deliver solutions that help organizations generate real value from data. From matching algorithms, to big data, to predictive analysis and machine learning, Growing Data can devise, design and implement a solution that generate new revenue and new capabilities for your organization. Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. At GrowingData, we have been working with “big data” for the past 10 years, from financial market data, through to hundreds of millions of transactions and terabytes of text data. We understand and have used platforms such a Red Shift, Hadoop all the way through to super computers to deliver systems that separate the signal from the noise…

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BIG DATA MANAGEMENT

Alation Named to Constellation ShortList for Metadata Management, Data Cataloging, & Data Governance for Second Consecutive Year

Alation | August 19, 2021

Alation Inc., the leader in enterprise data catalogs, today announced that it has been selected to the Constellation ShortList™ for Metadata Management, Data Cataloging & Data Governance in Q3 2021. The technology vendors and service providers included in this program deliver critical transformation initiative requirements for early adopter and fast follower organizations. “The ShortList™ is the first place business and technology leaders go for vendor selection, based on the collective view of Constellation’s clients, partners, and analysts who are on the front lines of understanding the technology landscape,” noted R “Ray” Wang, chairman and founder at Constellation Research. “Our analysts know that vendor selection is more of an art than a science and that the listed vendors all play a special role by industry, geography, and size of company. We know these are tough decisions and we hope this helps buyers get a head start. For those who want a detailed analysis, we are there to help with short advisory calls." Additionally, Alation customer Texas Mutual Insurance Company (TXM), the state's leading workers' compensation provider, has been named a finalist in the prestigious 2021 Constellation SuperNova Awards in the digital safety, governance, and privacy efforts category for its implementation of Alation. The SuperNova Awards recognize individuals and teams who are prioritizing disruptive technology and transforming their organizations with digital initiatives, achieving remarkable results, including competitive advantage, cost savings, and quantifiable improvements in agility. Customers like TXM have leaned on Alation to ensure the data behind each analysis is trustworthy and enable them to make critical business decisions rapidly. “It’s time to rethink data governance,” said Satyen Sangani, CEO and co-founder of Alation. “If companies are going to be agile in their decision-making, they need their data to be similarly responsive and agile. They also need to drive down the cost of compliance and regulation. A strong data governance program accelerates strategic decision-making and drives efficiency by putting governance capabilities into the day-to-day workflows of every employee.” Voting for the Constellation SuperNova Awards is open to the public. Polls close in a few short weeks on Sept. 3, 2021. To support TXM, click here to vote. This recognition comes on the heels of Alation being named a Leader in “The Forrester Wave™: Data Governance Solutions, Q3 2021” report and being named Snowflake’s Data Governance Partner of the Year. About Alation Alation is the leader in enterprise data intelligence solutions including data search & discovery, data governance, data stewardship, analytics, and digital transformation. Alation’s initial offering dominates the data catalog market. Thanks to its powerful Behavioral Analysis Engine, inbuilt collaboration capabilities, and open interfaces, Alation combines machine learning with human insight to successfully tackle even the most demanding challenges in data and metadata management. More than 280 enterprises drive data culture, improve decision making, and realize business outcomes with Alation including AbbVie, American Family Insurance, Cisco, Exelon, Fifth Third Bank, Finnair, Munich Re, NASDAQ, New Balance, Parexel, Pfizer, US Foods and Vistaprint. Headquartered in Silicon Valley, Alation was named to Inc. Magazine’s Best Workplaces list and is backed by leading venture capitalists including Blackstone, Costanoa, Data Collective, Dell Technologies, Icon, ISAI Cap, Riverwood, Salesforce, Sanabil, Sapphire, and Snowflake Ventures.

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WekaIO to Manage WeRide's AI Data Pipeline

WekaIO, Dasher | July 21, 2020

WekaIO™, the innovation leader in high-performance and scalable file storage, announced today that WeRide, a smart mobility company with industry-leading autonomous driving technologies, has selected the Weka File System (WekaFS™), the world’s fastest shared parallel file system from WekaIO, to manage its artificial intelligence (AI) data pipeline from the edge to the core to the cloud. WeRide implemented WekaFS using a hybrid model to manage compute and storage resources both on-premises using commodity Intel x86-based servers and in the Amazon Web Services (AWS) Cloud. WeRide chose WekaFS because it presented a hardware-agnostic solution that was also the most cost-efficient, delivering high-bandwidth I/O to the company’s GPU farm for high performance with mixed workloads. WeRide is a multi-faceted AI startup that works on advanced research and development (R&D) cycles for Level 4 (L4) autonomous driving vehicles and on partnerships with transportation platform providers that support robotaxi services for commuters. The company processes data at the petabyte (PB) level with a daily mix of large video and image files generated from mapping the operational design domain for the robotaxi service. The images are collected from more than 2 million kilometers of driving distance. WeRide produces millions of high-quality labeling data that is annotated at the core, trained by the AI model on the cloud-based cluster, and fed back to the on-premises AI engine.

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Neudata Launches MetaHub Storage Tool to Help Its Clients Manage and Store Metadata

Neudata | April 30, 2020

MetaHub, a metadata storage tool that allows clients to manage their entire library of traditional, market and alternative data sources in one place. MetaHub is comprised of two main functions - a metadata uploader tool and a data permissioning tool. Data stored within the MetaHub platform is inaccessible to any users outside the owner's organization, including members of the Neudata research team. Neudata has announced the launch of MetaHub, a metadata storage tool that allows clients to manage their entire library of traditional, market and alternative data sources in one, easy-to-access place. This Software-as-a-Service tool solves several problems related to data storage and management within large firms, including the generation of investment ideas for portfolio managers and analysts, the facilitation of alternative data adoption across different internal teams, and the organization of workflow and communication between central data strategy teams and various investment pods. - Rado Lipus, CEO and founder of Neudata These types of functionality are essential for data users across large organizations who want to organize and manage their approach to data, he added. MetaHub is comprised of two main functions - a metadata uploader tool and a data permissioning tool. Read more: GOOGLE DEBUTS NEW CLOUD STORAGE ARCHIVE CLASS FOR LONG-TERM DATA RETENTION The metadata uploader tool allows clients to add information on new datasets to the MetaHub platform, which shows up in user-generated reports that live alongside Neudata's library of over 3,500 datasets. Within these reports, users can annotate datasets, add and share key information like vendor contact details and pricing across the organization, and track dataset performance within their investment strategies over time. MetaHub's permissioning tool sets up admin users — who can add, change, and hide information about a dataset — and standard users, who are able to see the information that admins enable for them. This feature works particularly well if a centralized data team wants to manage the way that specific portfolio managers interact with the firm's data assets. - Rado Lipus, CEO and founder of Neudata Data stored within the MetaHub platform is inaccessible to any users outside the owner's organization, including members of the Neudata research team. All customer data is encrypted at rest using AES-GCM with 256-bit encryption keys and Neudata periodically reviews industry best practices to ensure algorithms and implementations are updated. Read more: DATADOBI EMERGES AS GEORGE JON'S FIRST CHOICE TO DELIVER DATA MIGRATION FOR ITS EDISCOVERY PLATFORM About Neudata: Founded in 2016 in London, Neudata is a human- and technology-powered data sourcing and research service that is completely independent — this means that it does not sell datasets or ask for revenue shares from data providers. Instead, its aim is to educate alternative data users and providers about new developments in the market. It also hopes to inspire new adopters across a spectrum of fundamental, quantamental and quant strategies, as well as those in the PE and corporate space.

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BIG DATA MANAGEMENT

Alation Named to Constellation ShortList for Metadata Management, Data Cataloging, & Data Governance for Second Consecutive Year

Alation | August 19, 2021

Alation Inc., the leader in enterprise data catalogs, today announced that it has been selected to the Constellation ShortList™ for Metadata Management, Data Cataloging & Data Governance in Q3 2021. The technology vendors and service providers included in this program deliver critical transformation initiative requirements for early adopter and fast follower organizations. “The ShortList™ is the first place business and technology leaders go for vendor selection, based on the collective view of Constellation’s clients, partners, and analysts who are on the front lines of understanding the technology landscape,” noted R “Ray” Wang, chairman and founder at Constellation Research. “Our analysts know that vendor selection is more of an art than a science and that the listed vendors all play a special role by industry, geography, and size of company. We know these are tough decisions and we hope this helps buyers get a head start. For those who want a detailed analysis, we are there to help with short advisory calls." Additionally, Alation customer Texas Mutual Insurance Company (TXM), the state's leading workers' compensation provider, has been named a finalist in the prestigious 2021 Constellation SuperNova Awards in the digital safety, governance, and privacy efforts category for its implementation of Alation. The SuperNova Awards recognize individuals and teams who are prioritizing disruptive technology and transforming their organizations with digital initiatives, achieving remarkable results, including competitive advantage, cost savings, and quantifiable improvements in agility. Customers like TXM have leaned on Alation to ensure the data behind each analysis is trustworthy and enable them to make critical business decisions rapidly. “It’s time to rethink data governance,” said Satyen Sangani, CEO and co-founder of Alation. “If companies are going to be agile in their decision-making, they need their data to be similarly responsive and agile. They also need to drive down the cost of compliance and regulation. A strong data governance program accelerates strategic decision-making and drives efficiency by putting governance capabilities into the day-to-day workflows of every employee.” Voting for the Constellation SuperNova Awards is open to the public. Polls close in a few short weeks on Sept. 3, 2021. To support TXM, click here to vote. This recognition comes on the heels of Alation being named a Leader in “The Forrester Wave™: Data Governance Solutions, Q3 2021” report and being named Snowflake’s Data Governance Partner of the Year. About Alation Alation is the leader in enterprise data intelligence solutions including data search & discovery, data governance, data stewardship, analytics, and digital transformation. Alation’s initial offering dominates the data catalog market. Thanks to its powerful Behavioral Analysis Engine, inbuilt collaboration capabilities, and open interfaces, Alation combines machine learning with human insight to successfully tackle even the most demanding challenges in data and metadata management. More than 280 enterprises drive data culture, improve decision making, and realize business outcomes with Alation including AbbVie, American Family Insurance, Cisco, Exelon, Fifth Third Bank, Finnair, Munich Re, NASDAQ, New Balance, Parexel, Pfizer, US Foods and Vistaprint. Headquartered in Silicon Valley, Alation was named to Inc. Magazine’s Best Workplaces list and is backed by leading venture capitalists including Blackstone, Costanoa, Data Collective, Dell Technologies, Icon, ISAI Cap, Riverwood, Salesforce, Sanabil, Sapphire, and Snowflake Ventures.

Read More

WekaIO to Manage WeRide's AI Data Pipeline

WekaIO, Dasher | July 21, 2020

WekaIO™, the innovation leader in high-performance and scalable file storage, announced today that WeRide, a smart mobility company with industry-leading autonomous driving technologies, has selected the Weka File System (WekaFS™), the world’s fastest shared parallel file system from WekaIO, to manage its artificial intelligence (AI) data pipeline from the edge to the core to the cloud. WeRide implemented WekaFS using a hybrid model to manage compute and storage resources both on-premises using commodity Intel x86-based servers and in the Amazon Web Services (AWS) Cloud. WeRide chose WekaFS because it presented a hardware-agnostic solution that was also the most cost-efficient, delivering high-bandwidth I/O to the company’s GPU farm for high performance with mixed workloads. WeRide is a multi-faceted AI startup that works on advanced research and development (R&D) cycles for Level 4 (L4) autonomous driving vehicles and on partnerships with transportation platform providers that support robotaxi services for commuters. The company processes data at the petabyte (PB) level with a daily mix of large video and image files generated from mapping the operational design domain for the robotaxi service. The images are collected from more than 2 million kilometers of driving distance. WeRide produces millions of high-quality labeling data that is annotated at the core, trained by the AI model on the cloud-based cluster, and fed back to the on-premises AI engine.

Read More

Neudata Launches MetaHub Storage Tool to Help Its Clients Manage and Store Metadata

Neudata | April 30, 2020

MetaHub, a metadata storage tool that allows clients to manage their entire library of traditional, market and alternative data sources in one place. MetaHub is comprised of two main functions - a metadata uploader tool and a data permissioning tool. Data stored within the MetaHub platform is inaccessible to any users outside the owner's organization, including members of the Neudata research team. Neudata has announced the launch of MetaHub, a metadata storage tool that allows clients to manage their entire library of traditional, market and alternative data sources in one, easy-to-access place. This Software-as-a-Service tool solves several problems related to data storage and management within large firms, including the generation of investment ideas for portfolio managers and analysts, the facilitation of alternative data adoption across different internal teams, and the organization of workflow and communication between central data strategy teams and various investment pods. - Rado Lipus, CEO and founder of Neudata These types of functionality are essential for data users across large organizations who want to organize and manage their approach to data, he added. MetaHub is comprised of two main functions - a metadata uploader tool and a data permissioning tool. Read more: GOOGLE DEBUTS NEW CLOUD STORAGE ARCHIVE CLASS FOR LONG-TERM DATA RETENTION The metadata uploader tool allows clients to add information on new datasets to the MetaHub platform, which shows up in user-generated reports that live alongside Neudata's library of over 3,500 datasets. Within these reports, users can annotate datasets, add and share key information like vendor contact details and pricing across the organization, and track dataset performance within their investment strategies over time. MetaHub's permissioning tool sets up admin users — who can add, change, and hide information about a dataset — and standard users, who are able to see the information that admins enable for them. This feature works particularly well if a centralized data team wants to manage the way that specific portfolio managers interact with the firm's data assets. - Rado Lipus, CEO and founder of Neudata Data stored within the MetaHub platform is inaccessible to any users outside the owner's organization, including members of the Neudata research team. All customer data is encrypted at rest using AES-GCM with 256-bit encryption keys and Neudata periodically reviews industry best practices to ensure algorithms and implementations are updated. Read more: DATADOBI EMERGES AS GEORGE JON'S FIRST CHOICE TO DELIVER DATA MIGRATION FOR ITS EDISCOVERY PLATFORM About Neudata: Founded in 2016 in London, Neudata is a human- and technology-powered data sourcing and research service that is completely independent — this means that it does not sell datasets or ask for revenue shares from data providers. Instead, its aim is to educate alternative data users and providers about new developments in the market. It also hopes to inspire new adopters across a spectrum of fundamental, quantamental and quant strategies, as well as those in the PE and corporate space.

Read More

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