Predictive Analytics: Implementation in Business Processes

Aashish Yadav | April 28, 2022 | 182 views

Predictive Analytics: Implementation in Business Processes
Knowledge is power in business, and knowing what will happen in the future is a superpower. When data analytics, statistical algorithms, AI, and machine learning are combined, this superpower, also known as predictive analytics, becomes a skill that can significantly influence on a company's choices and outcomes.

Predictive analytics is the use of modern analytical tools. For example, machine learning concludes about the future based on historical data. Businesses can consider application of predictive analytics tools and models to forecast trends and generate accurate future predictions by leveraging historical and current data. Let’s look at the top three reasons why predictive analytics is important for your business.

Why is Predictive Analytics Important for Businesses?

Businesses are looking at predictive analytics to help them solve challenges and discover new opportunities. Here are some of the most common benefits of predictive business analytics and an understanding of how is predictive analytics used in business.

Fraud Detection

In general, various analyzing techniques are merged to analyze data to enhance the accuracy of pattern recognition and discover criminal behavior, thereby reducing the incidence of frequent fraud. With behavioral analytics, you can look at any suspicious behavior and activities that happen on a network in real-time to look for fraud, zero-day breaches, and underlying threats.

Enhancing Business Campaigns

The predictive analytics process can help you optimize marketing campaigns and promotional events. Predictive designs helps businesses attract, retain, and increase valuable customers by determining their purchase responses and promoting cross-sell opportunities.

Minimizing Potential Risk

The predictive analytics process helps businesses decide on appropriate steps to avoid or reduce losses. Predictive analytics is revolutionizing risk management by alerting businesses about future developments. For example, credit scores, which financial institutions use to predict defaulters depending on a user's purchasing behavior.

How Does Predictive Analytics Help the C-Suite?

The C-suite is the final decision maker, so they are the ones who must use predictive analytics the most for insightful decision-making. Let’s look at ways in which predictive analytics can help C-level executives.


Predict Customer Behavior

Predictive analytics utilizes data to forecast future customer behavior. Customer intent becomes the primary aspect rather than historical transactional data, allowing for hyper-personalized marketing and communications. For example, researchers at China's Renmin University used predictive analytics and machine learning to figure out that data on consumer interests and jobs can predict customer preferences and purchase intent for cars.

Predicting customer requirements accurately is a huge opportunity for businesses. Companies can use AI and predictive analytics models to figure out what customers will do based on data instead of guesswork.


Pricing Optimization

Predictive business analytics can help companies improve pricing optimization quickly and affordably. A business can use predictive analytics to figure out how to make a product more affordable in the future by looking at past data, industry trends, competitive prices, and other data sources.

Each customer provides a unique value to the products. To add to the complexity, a consumer's value of a product may vary depending on the purchase circumstances and environment. Simplicity in pricing misses opportunities and can result in a significant drop in revenue.

Product information, consumer segmentation, and purchase circumstances are all enhanced by predictive analytics. Businesses can use this data to uncover trends and patterns to help them price more profitably.


Predicting Growth and Market Trends

Businesses can use predictive market analysis to decipher existing and future market trends. With this data, businesses can develop a plan to maximize opportunities, expand market share, and sustain disruption and new competition. Companies can use it to detect unmet customer demand and fill any gaps. Consumption sentiment is revealed through social media data. A product that does not match customer demand creates a market opportunity for a new product or service.

Predictive market analysis can uncover customer perceptions of a product or service and unmet consumer demands. Predictive business analytics helps businesses better understand their customers, meet their needs, and find new ways to earn revenue and grow.


Example: Reu La La Uses Predictive Analytics to Increase its Revenue by 10%

You often hear about giant enterprises like Amazon, Airbnb, Microsoft, Google, and others utilizing predictive analytics to extend their reach, boost sales, and more. Today let’s look at Reu La La and how they used predictive analytics to enhance their revenue.

Rue La La, a boutique retailer, often needs to predict sales and fix pricing for products being sold for the first time in its online store with no existing sales data. They observed that many products were either sold out within the first few hours of release or did not sell, which lead to revenue loss.

Rue La La took action by creating a set of quantitative qualities for its items and predicting future demand by utilizing historical sales data. They used statistical and computing technologies, such as regression analysis and machine learning, to create a demand forecast and pricing optimization model. In partnership with the Massachusetts Institute of Technology, they created an automated price decision assistance tool. Revenue increased from 10% to 13% across all departments because they used the pricing tool's proposed optimal rates.


Conclusion

“As data piles up, we have ourselves a genuine gold rush. But data isn’t the gold. I repeat, data in its raw form is boring crud. The gold is what’s discovered therein.”

Eric Siegel

You can consider the predictions that predictive analytics makes as gold, but, using predictive analytics is like a crystal ball that shows the future. You can look into the future, prevent issues in your company from escalating, and recognize profitable possibilities.

If you haven't started leveraging predictive analytics, start by experimenting with it on a modest scale and gradually build up as you acquire expertise and observe positive outcomes.


FAQ


How can Predictive Analytics Improve Performance Measurement?

Predictive analytics improves performance measurements by expanding an organization's understanding of the important performance drivers. It also helps with the weighting of different performance metrics based on how important they are.
 

What Are the Four Steps in Predictive Analytics?

In simple terms, predictive analytics involves four steps: creating a baseline prediction, assessing it, adding assumptions, and building a consensus demand plan. To do so, we must first choose a modeling technique, create a test design, then construct the model, evaluate the mode, and achieve alignment.
 

What Are the Three Different Types of Predictive Analytics?

Businesses utilize three forms of analytics to drive their decision-making:

Descriptive analytics — tells something that has already happened;
Predictive analytics — shows what can happen;
Prescriptive analytics — tells what should happen in the future

 

Spotlight

Data Science Council of America

The Data Science Council of America (DASCA) is an independent, third–party, international credentialing organization for Big Data professionals. DASCA credentialing programs for aspiring and working big data professionals are fleshed on the world's first vendor–neutral standards – the five–pronged DASCA Essential Knowledge Framework (EKF™). The EKF™ enunciates for both big data professionals and recruiters alike, a universal and standardized model of Essential Knowledge Prerequisites, which DASCA concludes as critical for big data professionals to possess if they desire to excel consistently in their jobs and establish themselves in the league of world's finest big data professionals.

OTHER ARTICLES
BIG DATA MANAGEMENT

How is Data Virtualization Shifting the Tailwind in Data Management?

Article | July 15, 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
BIG DATA MANAGEMENT

How Artificial Intelligence Is Transforming Businesses

Article | June 13, 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 | June 24, 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

Data Science Council of America

The Data Science Council of America (DASCA) is an independent, third–party, international credentialing organization for Big Data professionals. DASCA credentialing programs for aspiring and working big data professionals are fleshed on the world's first vendor–neutral standards – the five–pronged DASCA Essential Knowledge Framework (EKF™). The EKF™ enunciates for both big data professionals and recruiters alike, a universal and standardized model of Essential Knowledge Prerequisites, which DASCA concludes as critical for big data professionals to possess if they desire to excel consistently in their jobs and establish themselves in the league of world's finest big data professionals.

Related News

DATA VISUALIZATION, DATA ARCHITECTURE

Alteryx Ventures Announces Strategic Investment in MANTA

Alteryx | December 08, 2022

Alteryx, Inc., the Analytics Automation company, has announced a strategic investment in MANTA, the data lineage company. MANTA enables enterprises to achieve full visibility into the most complex data environments. With this investment from Alteryx Ventures, MANTA will be able to bolster product innovation, expand its partner ecosystem, and grow in key markets. Alteryx's investment in MANTA furthers the company's commitment to enterprise governance, risk, and compliance and accelerates joint product integration. MANTA empowers data professionals and IT departments to ensure data pipeline health across the enterprise. Alteryx's deep roots in enabling analytics democratization within many of the largest and most complex global enterprises makes it an ideal partner in establishing strong governance practices. Combined, the two companies create an end-to-end solution that enables organizations to deeply understand data lineage, including how data moves through a company, where it originated, how it is transformed and analyzed, and ultimately where it's used. This creates a meaningful audit trail for compliance. "We are excited to work with MANTA to help companies gain visibility into their data environments. Both companies share a common mission to enable analytics adoption at scale, The MANTA Data Lineage Platform will be a strong partner to our customers looking to efficiently grow their analytics footprint within their teams." Jay Henderson, SVP of Product Management, Alteryx Commenting on this partnership, Tomas Kratky, MANTA CEO and Founder, said, Data Lineage is becoming the cornerstone of a modern data management strategy and is at the core of advanced concepts like data fabric, enabling businesses to fully operationalize data and boost internal productivity. We are proud to partner with Alteryx to advance our innovation even further and support our growing customer base on their data journey. Alteryx Ventures invests in companies with innovative technology and services that complement Alteryx's analytics and data science products and encourage innovation within the analytics ecosystem. Alteryx's vision centers on enabling every person to achieve breakthrough outcomes from data through analytics automation, data science, and unprecedented ease of use. About MANTA MANTA is a world-class data lineage platform that helps fix your blind spots and offers a line of sight into your data environment. By automatically scanning your data environment, MANTA builds a powerful map of all data flows and delivers it through a native UI and other channels to both technical and non-technical users. With MANTA, everyone gets full visibility and control of their data pipeline. Visit getmanta.com to learn how MANTA can help your company leverage data as a true corporate asset. About Alteryx Alteryx powers analytics for all by providing our leading Analytics Automation Platform. Alteryx delivers easy end-to-end automation of data engineering, analytics, reporting, machine learning, and data science processes, enabling enterprises everywhere to democratize data analytics across their organizations for a broad range of use cases. More than 8,000 customers globally rely on Alteryx to deliver high-impact business outcomes.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Pico expands flagship monitoring platform into the cloud with the launch of Corvil Cloud Analytics

Pico | December 07, 2022

Pico, a leading provider of mission-critical technology services, software, data and analytics for the financial markets community, has expanded the reach and visibility of industry leading Corvil Analytics into the cloud with the launch of Corvil Cloud Analytics. Pico’s Corvil Analytics has a 20-plus year legacy across financial services in extracting and correlating technology and transaction performance intelligence from global dynamic network environments. Corvil’s high throughput, lossless, granularly time-stamped data capture provides an incredibly rich data source that can be used for broader analytics and use cases, including trade analytics. Corvil is available across multiple environments including colocation and on-prem, and now those same attributes that make Corvil Analytics an industry leader are available in the cloud with Corvil Cloud Analytics. “As companies look to move real-time applications to the cloud, they struggle with visibility when utilizing existing cloud monitoring solutions. “There is a need for deeper visibility to fill those voids, and Corvil Cloud Analytics is the solution, providing market-leading analytics for applications running in the cloud. Corvil Cloud Analytics provides our clients with the real-time analytics required to migrate their most critical workloads to the cloud, with confidence.” Stacie Swanstrom, Chief Product Officer at Pico Highlights of Corvil Cloud Analytics include: Maximum Visibility: Measures every order, every market data tick and every packet to fill the missing gap of visibility needed to manage real-time performance in public cloud environments Granular Instrumentation: Provides per-packet and per-application message analytics alongside Corvil’s AppAgent to instrument internal application performance Corvil Analytics: Provides all functions of Corvil Analytics including network congestion analytics for public cloud infrastructure, and per-hop trading and market data analytics for cloud-hosted deployments Flexibility: Pay for only what is needed in the public cloud Corvil Analytics is currently used by the world’s largest banks, exchanges, electronic market makers, quantitative hedge funds, data service providers and brokers. With the launch of Corvil Cloud Analytics, and as exchanges partner with the major cloud providers to bring trading into the cloud, Corvil can now provide a single pane of glass for monitoring colocation, on-prem and cloud environments together. “We had the vision to provide clients the same technology, visibility and rich analytics they’ve come to rely on through Corvil,” Swanstrom said. “Since Corvil Cloud Analytics is software only, this accelerates our deployments and also provides an expedited avenue for proof-of-concept use cases. It’s now easier than ever for clients to access the platform so they can see firsthand what makes Corvil an industry leader in data analytics.” Corvil Cloud Analytics provides the highly granular, real-time Corvil visibility required to understand the cause of variable performance that continues to impact real-time applications running in the public cloud. With cloud applications, there is no hardware CapEx costs, lead times, or shipping and installation challenges. Corvil Cloud Analytics is simple to scale, easy to deploy and can be up and running in hours instead of weeks. Corvil’s industry leading visibility and intelligence is now available for businesses wanting the competitive edge in the cloud. About Pico Pico is a leading provider of technology services for the financial markets community. Pico provides a best-in-class portfolio of innovative, transparent, low-latency markets solutions coupled with an agile and expert service delivery model. Instant access to financial markets is provided via PicoNet™, a globally comprehensive network platform instrumented natively with Corvil to generate analytics and telemetry. Clients choose Pico when they want the freedom to move fast and create an operational edge in the fast-paced world of financial markets.

Read More

DATA VISUALIZATION

Opaque Systems, Pioneer in Confidential Computing, Unveils the First Multi-Party Confidential AI and Analytics Platform

Opaque Systems | December 08, 2022

Opaque Systems, the pioneers of secure multi-party analytics and AI for Confidential Computing, today announced the latest advancements in Confidential AI and Analytics with the unveiling of its platform. The Opaque platform, built to unlock use cases in Confidential Computing, is created by the inventors of the popular MC2 open source project which was conceived in the RISELab at UC Berkeley. The Opaque Platform uniquely enables data scientists within and across organizations to securely share data and perform collaborative analytics directly on encrypted data protected by Trusted Execution Environments (TEEs). The platform further accelerates Confidential Computing use cases by enabling data scientists to leverage their existing SQL and Python skills to run analytics and machine learning while working with confidential data, overcoming the data analytics challenges inherent in TEEs due to their strict protection of how data is accessed and used. The Opaque platform advancements come on the heels of Opaque announcing its $22M Series A funding, Confidential Computing – projected to be a $54B market by 2026 by the Everest Group – provides a solution using TEEs or 'enclaves' that encrypt data during computation, isolating it from access, exposure and threats. However, TEEs have historically been challenging for data scientists due to the restricted access to data, lack of tools that enable data sharing and collaborative analytics, and the highly specialized skills needed to work with data encrypted in TEEs. The Opaque Platform overcomes these challenges by providing the first multi-party confidential analytics and AI solution that makes it possible to run frictionless analytics on encrypted data within TEEs, enable secure data sharing, and for the first time, enable multiple parties to perform collaborative analytics while ensuring each party only has access to the data they own. "Traditional approaches for protecting data and managing data privacy leave data exposed and at risk when being processed by applications, analytics, and machine learning (ML) models, The Opaque Confidential AI and Analytics Platform solves this challenge by enabling data scientists and analysts to perform scalable, secure analytics and machine learning directly on encrypted data within enclaves to unlock Confidential Computing use cases." -Rishabh Poddar, Co-founder & CEO, Opaque Systems. Strict privacy regulations result in sensitive data being difficult to access and analyze, said a Data Science Leader at a top US bank. New multi-party secure analytics and computational capabilities and Privacy Enhancing Technology from Opaque Systems will significantly improve the accuracy of AI/ML/NLP models and speed insights. The Opaque Confidential AI and Analytics Platform is designed to specifically ensure that both code and data within enclaves are inaccessible to other users or processes that are collocated on the system. Organizations can encrypt their confidential data on-premises, accelerate the transition of sensitive workloads to enclaves in Confidential Computing Clouds, and analyze encrypted data while ensuring it is never unencrypted during the lifecycle of the computation. Key capabilities and advancements include: Secure, Multi-Party Collaborative Analytics – Multiple data owners can pool their encrypted data together in the cloud, and jointly analyze the collective data without compromising confidentiality. Policy enforcement capabilities ensure the data owned by each party is never exposed to other data owners. Secure Data Sharing and Data Privacy – Teams across departments and across organizations can securely share data protected in TEEs while adhering to regulatory and compliance policies. Use cases requiring confidential data sharing include financial crime, drug research, ad targeting monetization and more. Data Protection Throughout the Lifecycle – Protects all sensitive data, including PII and SHI data, using advanced encryption and secure hardware enclave technology, throughout the lifecycle of computation—from data upload, to analytics and insights. Multi-tiered Security, Policy Enforcement, and Governance – Leverages multiple layers of security, including Intel® Software Guard Extensions, secure enclaves, advanced cryptography and policy enforcement to provide defense in depth, ensuring code integrity, data, and side-channel attack protection. Scalability and Orchestration of Enclave Clusters – Provides distributed confidential data processing across managed TEE clusters and automates orchestration of clusters overcoming performance and scaling challenges and supports secure inter-enclave communication. Confidential Computing is supported by all major cloud vendors including Microsoft Azure, Google Cloud and Amazon Web Services and major chip manufacturers including Intel and AMD. About Opaque Systems: Commercializing the open source MC2 technology invented at UC Berkeley by its founders, Opaque System provides the first collaborative analytics and AI platform for Confidential Computing. Opaque uniquely enables data to be securely shared and analyzed by multiple parties while maintaining complete confidentiality and protecting data end-to-end. The Opaque Platform leverages a novel combination of two key technologies layered on top of state-of-the-art cloud security—secure hardware enclaves and cryptographic fortification. This combination ensures that the overall computation is secure, fast, and scalable. The MC2 technology and Opaque innovation has already been adopted by several organizations, such as Ant Group, IBM, Scotiabank, and Ericsson.

Read More

DATA VISUALIZATION, DATA ARCHITECTURE

Alteryx Ventures Announces Strategic Investment in MANTA

Alteryx | December 08, 2022

Alteryx, Inc., the Analytics Automation company, has announced a strategic investment in MANTA, the data lineage company. MANTA enables enterprises to achieve full visibility into the most complex data environments. With this investment from Alteryx Ventures, MANTA will be able to bolster product innovation, expand its partner ecosystem, and grow in key markets. Alteryx's investment in MANTA furthers the company's commitment to enterprise governance, risk, and compliance and accelerates joint product integration. MANTA empowers data professionals and IT departments to ensure data pipeline health across the enterprise. Alteryx's deep roots in enabling analytics democratization within many of the largest and most complex global enterprises makes it an ideal partner in establishing strong governance practices. Combined, the two companies create an end-to-end solution that enables organizations to deeply understand data lineage, including how data moves through a company, where it originated, how it is transformed and analyzed, and ultimately where it's used. This creates a meaningful audit trail for compliance. "We are excited to work with MANTA to help companies gain visibility into their data environments. Both companies share a common mission to enable analytics adoption at scale, The MANTA Data Lineage Platform will be a strong partner to our customers looking to efficiently grow their analytics footprint within their teams." Jay Henderson, SVP of Product Management, Alteryx Commenting on this partnership, Tomas Kratky, MANTA CEO and Founder, said, Data Lineage is becoming the cornerstone of a modern data management strategy and is at the core of advanced concepts like data fabric, enabling businesses to fully operationalize data and boost internal productivity. We are proud to partner with Alteryx to advance our innovation even further and support our growing customer base on their data journey. Alteryx Ventures invests in companies with innovative technology and services that complement Alteryx's analytics and data science products and encourage innovation within the analytics ecosystem. Alteryx's vision centers on enabling every person to achieve breakthrough outcomes from data through analytics automation, data science, and unprecedented ease of use. About MANTA MANTA is a world-class data lineage platform that helps fix your blind spots and offers a line of sight into your data environment. By automatically scanning your data environment, MANTA builds a powerful map of all data flows and delivers it through a native UI and other channels to both technical and non-technical users. With MANTA, everyone gets full visibility and control of their data pipeline. Visit getmanta.com to learn how MANTA can help your company leverage data as a true corporate asset. About Alteryx Alteryx powers analytics for all by providing our leading Analytics Automation Platform. Alteryx delivers easy end-to-end automation of data engineering, analytics, reporting, machine learning, and data science processes, enabling enterprises everywhere to democratize data analytics across their organizations for a broad range of use cases. More than 8,000 customers globally rely on Alteryx to deliver high-impact business outcomes.

Read More

BUSINESS INTELLIGENCE, BIG DATA MANAGEMENT

Pico expands flagship monitoring platform into the cloud with the launch of Corvil Cloud Analytics

Pico | December 07, 2022

Pico, a leading provider of mission-critical technology services, software, data and analytics for the financial markets community, has expanded the reach and visibility of industry leading Corvil Analytics into the cloud with the launch of Corvil Cloud Analytics. Pico’s Corvil Analytics has a 20-plus year legacy across financial services in extracting and correlating technology and transaction performance intelligence from global dynamic network environments. Corvil’s high throughput, lossless, granularly time-stamped data capture provides an incredibly rich data source that can be used for broader analytics and use cases, including trade analytics. Corvil is available across multiple environments including colocation and on-prem, and now those same attributes that make Corvil Analytics an industry leader are available in the cloud with Corvil Cloud Analytics. “As companies look to move real-time applications to the cloud, they struggle with visibility when utilizing existing cloud monitoring solutions. “There is a need for deeper visibility to fill those voids, and Corvil Cloud Analytics is the solution, providing market-leading analytics for applications running in the cloud. Corvil Cloud Analytics provides our clients with the real-time analytics required to migrate their most critical workloads to the cloud, with confidence.” Stacie Swanstrom, Chief Product Officer at Pico Highlights of Corvil Cloud Analytics include: Maximum Visibility: Measures every order, every market data tick and every packet to fill the missing gap of visibility needed to manage real-time performance in public cloud environments Granular Instrumentation: Provides per-packet and per-application message analytics alongside Corvil’s AppAgent to instrument internal application performance Corvil Analytics: Provides all functions of Corvil Analytics including network congestion analytics for public cloud infrastructure, and per-hop trading and market data analytics for cloud-hosted deployments Flexibility: Pay for only what is needed in the public cloud Corvil Analytics is currently used by the world’s largest banks, exchanges, electronic market makers, quantitative hedge funds, data service providers and brokers. With the launch of Corvil Cloud Analytics, and as exchanges partner with the major cloud providers to bring trading into the cloud, Corvil can now provide a single pane of glass for monitoring colocation, on-prem and cloud environments together. “We had the vision to provide clients the same technology, visibility and rich analytics they’ve come to rely on through Corvil,” Swanstrom said. “Since Corvil Cloud Analytics is software only, this accelerates our deployments and also provides an expedited avenue for proof-of-concept use cases. It’s now easier than ever for clients to access the platform so they can see firsthand what makes Corvil an industry leader in data analytics.” Corvil Cloud Analytics provides the highly granular, real-time Corvil visibility required to understand the cause of variable performance that continues to impact real-time applications running in the public cloud. With cloud applications, there is no hardware CapEx costs, lead times, or shipping and installation challenges. Corvil Cloud Analytics is simple to scale, easy to deploy and can be up and running in hours instead of weeks. Corvil’s industry leading visibility and intelligence is now available for businesses wanting the competitive edge in the cloud. About Pico Pico is a leading provider of technology services for the financial markets community. Pico provides a best-in-class portfolio of innovative, transparent, low-latency markets solutions coupled with an agile and expert service delivery model. Instant access to financial markets is provided via PicoNet™, a globally comprehensive network platform instrumented natively with Corvil to generate analytics and telemetry. Clients choose Pico when they want the freedom to move fast and create an operational edge in the fast-paced world of financial markets.

Read More

DATA VISUALIZATION

Opaque Systems, Pioneer in Confidential Computing, Unveils the First Multi-Party Confidential AI and Analytics Platform

Opaque Systems | December 08, 2022

Opaque Systems, the pioneers of secure multi-party analytics and AI for Confidential Computing, today announced the latest advancements in Confidential AI and Analytics with the unveiling of its platform. The Opaque platform, built to unlock use cases in Confidential Computing, is created by the inventors of the popular MC2 open source project which was conceived in the RISELab at UC Berkeley. The Opaque Platform uniquely enables data scientists within and across organizations to securely share data and perform collaborative analytics directly on encrypted data protected by Trusted Execution Environments (TEEs). The platform further accelerates Confidential Computing use cases by enabling data scientists to leverage their existing SQL and Python skills to run analytics and machine learning while working with confidential data, overcoming the data analytics challenges inherent in TEEs due to their strict protection of how data is accessed and used. The Opaque platform advancements come on the heels of Opaque announcing its $22M Series A funding, Confidential Computing – projected to be a $54B market by 2026 by the Everest Group – provides a solution using TEEs or 'enclaves' that encrypt data during computation, isolating it from access, exposure and threats. However, TEEs have historically been challenging for data scientists due to the restricted access to data, lack of tools that enable data sharing and collaborative analytics, and the highly specialized skills needed to work with data encrypted in TEEs. The Opaque Platform overcomes these challenges by providing the first multi-party confidential analytics and AI solution that makes it possible to run frictionless analytics on encrypted data within TEEs, enable secure data sharing, and for the first time, enable multiple parties to perform collaborative analytics while ensuring each party only has access to the data they own. "Traditional approaches for protecting data and managing data privacy leave data exposed and at risk when being processed by applications, analytics, and machine learning (ML) models, The Opaque Confidential AI and Analytics Platform solves this challenge by enabling data scientists and analysts to perform scalable, secure analytics and machine learning directly on encrypted data within enclaves to unlock Confidential Computing use cases." -Rishabh Poddar, Co-founder & CEO, Opaque Systems. Strict privacy regulations result in sensitive data being difficult to access and analyze, said a Data Science Leader at a top US bank. New multi-party secure analytics and computational capabilities and Privacy Enhancing Technology from Opaque Systems will significantly improve the accuracy of AI/ML/NLP models and speed insights. The Opaque Confidential AI and Analytics Platform is designed to specifically ensure that both code and data within enclaves are inaccessible to other users or processes that are collocated on the system. Organizations can encrypt their confidential data on-premises, accelerate the transition of sensitive workloads to enclaves in Confidential Computing Clouds, and analyze encrypted data while ensuring it is never unencrypted during the lifecycle of the computation. Key capabilities and advancements include: Secure, Multi-Party Collaborative Analytics – Multiple data owners can pool their encrypted data together in the cloud, and jointly analyze the collective data without compromising confidentiality. Policy enforcement capabilities ensure the data owned by each party is never exposed to other data owners. Secure Data Sharing and Data Privacy – Teams across departments and across organizations can securely share data protected in TEEs while adhering to regulatory and compliance policies. Use cases requiring confidential data sharing include financial crime, drug research, ad targeting monetization and more. Data Protection Throughout the Lifecycle – Protects all sensitive data, including PII and SHI data, using advanced encryption and secure hardware enclave technology, throughout the lifecycle of computation—from data upload, to analytics and insights. Multi-tiered Security, Policy Enforcement, and Governance – Leverages multiple layers of security, including Intel® Software Guard Extensions, secure enclaves, advanced cryptography and policy enforcement to provide defense in depth, ensuring code integrity, data, and side-channel attack protection. Scalability and Orchestration of Enclave Clusters – Provides distributed confidential data processing across managed TEE clusters and automates orchestration of clusters overcoming performance and scaling challenges and supports secure inter-enclave communication. Confidential Computing is supported by all major cloud vendors including Microsoft Azure, Google Cloud and Amazon Web Services and major chip manufacturers including Intel and AMD. About Opaque Systems: Commercializing the open source MC2 technology invented at UC Berkeley by its founders, Opaque System provides the first collaborative analytics and AI platform for Confidential Computing. Opaque uniquely enables data to be securely shared and analyzed by multiple parties while maintaining complete confidentiality and protecting data end-to-end. The Opaque Platform leverages a novel combination of two key technologies layered on top of state-of-the-art cloud security—secure hardware enclaves and cryptographic fortification. This combination ensures that the overall computation is secure, fast, and scalable. The MC2 technology and Opaque innovation has already been adopted by several organizations, such as Ant Group, IBM, Scotiabank, and Ericsson.

Read More

Events