Data analysis – Open Dice http://opendice.net/ Tue, 22 Nov 2022 16:58:39 +0000 en-US hourly 1 https://wordpress.org/?v=5.9.3 https://opendice.net/wp-content/uploads/2021/10/icon-6-120x120.png Data analysis – Open Dice http://opendice.net/ 32 32 The DOJ, the SEC, Insider Trading, and Data Analytics | Foley Hoag LLP – White Collar Law and Investigations https://opendice.net/the-doj-the-sec-insider-trading-and-data-analytics-foley-hoag-llp-white-collar-law-and-investigations/ Tue, 22 Nov 2022 16:58:39 +0000 https://opendice.net/the-doj-the-sec-insider-trading-and-data-analytics-foley-hoag-llp-white-collar-law-and-investigations/ A year ago, the Department of Justice (“DOJ”) and the Securities and Exchange Commission (“SEC”) announced the analysis of the data announcing parallel insider trading actions against a senior executive of a pharmaceutical company (Viatris Inc.), formerly known as Mylan NV (“Mylan”). The SEC claimed that “efforts to conceal the scheme via secure messaging apps […]]]>

A year ago, the Department of Justice (“DOJ”) and the Securities and Exchange Commission (“SEC”) announced the analysis of the data announcing parallel insider trading actions against a senior executive of a pharmaceutical company (Viatris Inc.), formerly known as Mylan NV (“Mylan”). The SEC claimed that “efforts to conceal the scheme via secure messaging apps and foreign cash payments were unsuccessful, as this case highlights the agency’s ability to use sophisticated data analysis to detect suspicious trading patterns and identify the traders behind them”.

Last year the case was against the alleged tippee, this year against the alleged tipper. On Nov. 10, 2022, the SEC and DOJ filed suit against the alleged dumpster based on many of the same underlying facts as the previous case. Neither action reveals on its face whether the second case is the product of traditional investigative techniques, cooperation, or additional data analysis. Here are the alleged facts.

The most recently charged individual, Ramkumar Rayapureddy, oversaw Mylan’s information technology (“IT”) operations as Mylan’s “Chief Information Officer” during the relevant period. The DOJ and SEC allege that Rayapureddy provided material, nonpublic information about Mylan to Dayakar Mallu, who also worked in Mylan’s IT department and who traded securities based on that information. Three separate boards are alleged.

The first alleged tip related to Mylan’s announcement of FDA approval in September 2017. According to the DOJ and SEC, “expecting the announcement to have a positive impact on the stock price of Mylan,” Rayapureddy informed Mallu in a phone call that Mylan was going to publicly announce that it has received FDA approval for a generic version of a multiple sclerosis drug. On the same day, Mallu reportedly purchased around 1,000 Mylan call option contracts.

Second, the two agencies allege that Rayapureddy informed Mallu that Mylan would report financial results below market expectations for the fourth quarter and full year of 2018. Rayapureddy used “a secure messaging and calling app” to give that advice, according to the SEC complaint. Mallu reportedly closed its existing put option contracts ahead of the announcement, avoiding around $700,000 in losses.

Third, the agencies allege that Rayapureddy kept Mallu informed about a possible merger with one of Pfizer’s businesses in mid-2019. In particular, Rayapureddy reportedly briefed Mallu on the timing of the transaction and said he believed the transaction would be well received by the market. Based on this information, Mallu is said to have purchased over 13,000 call options on Mylan and made over $7 million in gains from these insider trades. The DOJ and SEC also allege that Mallu shared some of those profits with Rayapureddy by making cash payments to Rayapureddy and Rayapureddy’s designees in India.

The DOJ charged Rayapureddy with conspiracy to commit securities fraud and three counts of securities fraud. Rayapureddy pleaded not guilty, according to the court filing. The SEC also alleges that Rayapureddy violated Section 10(b) of the Exchange Act and Rule 10b-5 thereunder. The DOJ and SEC indicted Mallu in September 2021. Mallu pleaded guilty to conspiracy to commit securities fraud, as well as assisting in the preparation of a false tax return.

Last summer, the SEC indicted nine people in connection with three separate alleged insider trading schemes, all based on its use of “data analytics tools to detect suspicious trading patterns.” The SEC has a special unit, the Center for Analysis and Detection of the Market Abuse Unit. Although not new, the unit is obviously active. The government is likely to continue to rely on data analytics to investigate and impose insider trading enforcement.

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Data Analysis of Wired Blood Pressure Monitors Market and Key Industry Players by 2028 – The C-Drone Review https://opendice.net/data-analysis-of-wired-blood-pressure-monitors-market-and-key-industry-players-by-2028-the-c-drone-review/ Thu, 17 Nov 2022 03:08:34 +0000 https://opendice.net/data-analysis-of-wired-blood-pressure-monitors-market-and-key-industry-players-by-2028-the-c-drone-review/ Global Wired Blood Pressure Monitors Market 2022 Significantly Assessed By MarketsandResearch.biz to get the overall global market position for the forecast year 2022-2028. SWOT analysis tool that can help you analyze which company is doing the best right now and what opportunities are available in the market keeping in mind the threats of the need […]]]>

Global Wired Blood Pressure Monitors Market 2022 Significantly Assessed By MarketsandResearch.biz to get the overall global market position for the forecast year 2022-2028. SWOT analysis tool that can help you analyze which company is doing the best right now and what opportunities are available in the market keeping in mind the threats of the need to design a successful strategy for the future on the wired blood pressure monitor market

DOWNLOAD FREE SAMPLE REPORT: https://www.marketsandresearch.biz/sample-request/321016

Le rapport présente une analyse approfondie de l’analyse PESTEL[politiqueéconomiquesocialetechnologiqueenvironnementaleetjuridique)ilpermetàl’entreprisedesefaireuneidéedesfacteursquiaffectentunenouvelleentrepriseetd’identifierlesfacteursderisquedumarchéTensiomètrecâbléLeprofilaged’entreprisededifférentesentreprisesestégalementmentionnéquifournitunplandétaillédelastructureorganisationnelle:aperçudel’entrepriseaperçudel’entrepriseanalysedespartsdemarchéportefeuilledéveloppementrécentfusionetacquisitionetanalyse[politicaleconomicalsocialtechnologicalenvironmentalandlegal)itallowsthecompanytoformanimpressionofthefactorsthataffectanewventureandidentifyriskfactorsoftheWiredBloodPressureMonitormarketCorporateprofilingofdifferentcompaniesisalsomentionedthatdeliversanin-depthblueprintoftheorganizationalstructure:theBusinessoverviewcompanysnapshotmarketshareanalysisportfoliorecentdevelopmentmergerandacquisitionandanalysis[politiqueéconomiquesocialetechnologiqueenvironnementaleetjuridique)ilpermetàl’entreprisedesefaireuneidéedesfacteursquiaffectentunenouvelleentrepriseetd’identifierlesfacteursderisquedumarchéTensiomètrecâbléLeprofilaged’entreprisededifférentesentreprisesestégalementmentionnéquifournitunplandétaillédelastructureorganisationnelle :aperçudel’entrepriseaperçudel’entrepriseanalysedespartsdemarchéportefeuilledéveloppementrécentfusionetacquisitionetanalyse[politicaleconomicalsocialtechnologicalenvironmentalandlegal)itallowsthecompanytoformanimpressionofthefactorsthataffectanewventureandidentifyriskfactorsoftheWiredBloodPressureMonitormarketCorporateprofilingofdifferentcompaniesisalsomentionedthatdeliversanin-depthblueprintoftheorganizationalstructure:theBusinessoverviewcompanysnapshotmarketshareanalysisportfoliorecentdevelopmentmergerandacquisitionandanalysis

Many tests are carried out. The CAGR (compound annual growth rate) is calculated in the most accurate way to determine that the value can increase or decrease over a period of time. Investors can easily compare the CAGR of two to the performance of one against the other using attractive graphs. in the wired blood pressure monitor market. This will help stakeholders evaluate the business plan, develop policies and implement them in the market.

Segmentation Analysis Covered by Wired Blood Pressure Monitors Market

The study represents the geographical area

  • North America (United States, Canada and Mexico)
  • Europe (Germany, France, UK, Russia, Italy and Rest of Europe)
  • Asia-Pacific (China, Japan, Korea, India, Southeast Asia and Australia)
  • South America (Brazil, Argentina, Colombia and rest of South America)
  • Middle East and Africa (Saudi Arabia, United Arab Emirates, Egypt, South Africa and Rest of Middle East and Africa)

The report provides industry competitors

  • OMRON
  • AD
  • Microlife
  • Healthandlife
  • Rossmax
  • panasonic
  • NISSEI
  • Citizen
  • Hill-Rom
  • And on
  • Yuwell
  • Yield King
  • gracemedical
  • Pango
  • Boumi
  • medical automatic control
  • Briggs Health
  • Meditech
  • Sejoy
  • New medical item
  • Transtek
  • Withing
  • Easy Med Instruments

ACCESS FULL REPORT: https://www.marketsandresearch.biz/report/321016/global-wired-blood-pressure-monitor-market-2022-by-manufacturers-regions-type-and-application-forecast-to-2028

By product classification covered in the report

  • Upper Arm Blood Pressure Monitor
  • wrist blood pressure monitor

The file explains the application of the market

Report customization:

This report can be customized to meet customer requirements. Please contact our sales team (sales@marketsandresearch.biz), who will ensure that you get a report that suits your needs. You can also get in touch with our executives at +1-201-465-4211 to share your research needs.

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How Process Mining Became an Integral Part of the Data Analytics Toolkit Landscape https://opendice.net/how-process-mining-became-an-integral-part-of-the-data-analytics-toolkit-landscape/ Wed, 09 Nov 2022 15:30:00 +0000 https://opendice.net/how-process-mining-became-an-integral-part-of-the-data-analytics-toolkit-landscape/ In this analyst shot, Kieron Allen reports from Munich, Germany, where he is attending the Celosphere 2022 conference, and shares some details about the topics, companies, and events he is looking forward to and looking forward to. will cover in the next few days. This analyst take is sponsored by Celonis, the market leader in […]]]>

In this analyst shot, Kieron Allen reports from Munich, Germany, where he is attending the Celosphere 2022 conference, and shares some details about the topics, companies, and events he is looking forward to and looking forward to. will cover in the next few days.

This analyst take is sponsored by Celonis, the market leader in process mining and execution management. Join the world’s top 2,000 process fanatics and learn how to fix process inefficiencies at Celosphere, the company’s annual conference November 9e and 10e in Munich, Germany. Sign up to watch Celosphere 2022 free virtual live stream here.

Strong points

00:22 — Kieron and Tom Smith will post daily Celosphere content. Specifically, Kieron will learn how process mining has become an integral part of the data analysis landscape and toolkit.

00:42 — At Celosphere, Kieron will hear from industry giants, such as IBM, Aviana Airlines and IKEA, about how slowness allows these companies to visualize the inner workings and connections of every business process.

1:01 — This week, Kieron is excited to share with Accelerating Economy subscribers how their companies can leverage existing and upcoming process mining techniques to support their efforts in an Accelerating Economy.

01:14 — There will be more to come this week from Celosphere on how users can leverage process mining tools to accelerate their digital presence and process data the way industry giants do.


For more exclusive coverage of innovative cloud companies, check out Cloud Wars Horizon here:

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Accelerating Scientific Discovery with Data Analytics Platforms https://opendice.net/accelerating-scientific-discovery-with-data-analytics-platforms/ Thu, 03 Nov 2022 18:31:00 +0000 https://opendice.net/accelerating-scientific-discovery-with-data-analytics-platforms/ In this interview, we talk to Victor Wong, Scientific Director of Core Life Analytics, about their StratoMineRMT product and how it helps researchers quickly process their data. Could you introduce yourself and tell us about your journey to Core Life Analytics? My name is Victor and I started my scientific career at the University of […]]]>

In this interview, we talk to Victor Wong, Scientific Director of Core Life Analytics, about their StratoMineRMT product and how it helps researchers quickly process their data.

Could you introduce yourself and tell us about your journey to Core Life Analytics?

My name is Victor and I started my scientific career at the University of Toronto, where I obtained my doctorate in physiology. I then focused on metabolic disorders, with an emphasis on drug targets and drug discovery. I then worked as a postdoc in neuroscience at UC Davis and Weill Cornell Medical Center. At the latter institution, I was exposed to high-throughput, high-content imaging, using compound screens for drug discovery.

My naivety at first gave me the false impression that automation would dramatically speed up my projects and posts, but that just wasn’t the case. Data analysis was the biggest challenge; the amount of data coming from my projects was beyond my knowledge to even know where to start. I tried to get some proficiency in programming, but nothing was ever robust or repeatable.

I joined Core Life Analytics simply because they are the solution to the data problem I had. Additionally, our scientific philosophies align incredibly well: to provide robust and transparent data analysis tools that allow scientists to quickly analyze their data and paint a holistic picture of their experiments. In addition, and above all, to make scientists aware of good practices in data science.

What are the main purposes of Core Life Analytics and how does it fit into the broader field of biological and life sciences?

At Core Life Analytics, we are on a mission to democratize data science: we help biologists analyze their complex phenotypic data independently.

High-content or phenotypic screening is a powerful tool for drug discovery. Using advanced microscopes and image analysis software, scientists can translate microscopic images into hundreds or thousands of measurements of a cell’s morphology, such as size, intensity, and shape. These so-called characteristics describe and quantify a cell’s phenotype, allowing researchers to carefully assess a compound’s effect.

Techniques like these are part of a move towards more data-driven approaches: instead of focusing on metrics you know are involved in the processes you’re studying, measure them all and use statistics to determine what is interesting.

Image Credit: Gorodenkoff/Shutterstock.com

The rise of data analytics and bioinformatics is prevalent in all areas of biological and life sciences, but many still struggle to integrate it into their workflow. What are the main obstacles that limit the use of advanced data analysis software in these sectors?

Most scientists find it difficult to use these datasets. Our founders, David Egan and Wienand Omta, witnessed this firsthand at the UMC Utrecht Cell Screening Core; their clients either had to learn data science and coding skills to analyze their data, or have a data scientist do it for them. In both cases, the data is underutilized. Often only a handful of known metrics are analyzed, leaving behind hundreds or thousands of potentially useful metrics.

Why should biologists strive to use advanced data analytics platforms, and how can this help catalyze innovation in areas like drug discovery?

Giving biologists the tools to perform their analyzes autonomously greatly improves the speed with which discoveries are made. First, biologists no longer have to wait for busy data scientists or learn to code, but can simply run their data through the analytics platform.

Second, it allows the person who knows the experiments best – who designed and ran them – to explore the data and make decisions for future experiments accordingly. This is not only important for the final analysis of an experiment; Being able to quickly run these analyzes in the early experimental stages of a study allows you to assess the quality of your model or test and identify problems early on.

Don’t forget the data scientists; When biologists perform these relatively routine analyzes themselves, they have time for the more exciting things, such as advanced AI and multi-omics.

StratoMine®MT is the core product of Core Life Analytics that aims to help researchers quickly process their data. Could you discuss the background of this product and how users can integrate it into their workflow?

When David Egan and Wienand Omta realized at UMC Utrecht that the need for accessible data analysis tools was widespread, they decided to develop something that could be used by any biologist dealing with this type of data. No matter what hardware or software they use or their data science skills. Simply upload your digital data and StratoMineR guides you through a best practice workflow for phenotypic data.

Starting with the most basic steps, such as finding relevant features, quality checking, normalizing and scaling your data, to more advanced steps, like data reduction, to optionally compare and group phenotypes to determine a compound’s mechanism of action.

How StratoMineR worksMT compare to existing platforms currently available? Are there any components that end users would find particularly interesting?

What differentiates our approach from other tools is that it is intuitive and decision-supporting. StratoMineR’s guided workflow ensures no steps are missed and offers suggestions using AI where possible. This way, any biologist can follow, understand, and explore a best practice analysis workflow for multiparameter data. And start doing it early in the experimental phase of a project.

Core Life Analytics recently participated in ELRIG Drug Discovery, Europe’s largest meeting bringing together life science industry professionals. What are the benefits of attending such events to discuss and demonstrate products in person?

ELRIG Drug Discovery was an excellent meeting with an excellent scientific program. We always appreciate meetings like these, as they are a perfect opportunity to catch up on the latest developments in the field. More importantly, we can talk to scientists from many different backgrounds and learn about their perspectives and challenges.

There are many advancements being made in data science technologies, and all industries are reaping the benefits. How do you think the relationship between data science and the life sciences industry will evolve over the next ten years?

As mentioned earlier, interest in data-driven drug discovery is growing. A good illustration of this is the JUMP-CP consortium, which generated a database of phenotypic data from cells responding to 140,000 different genetic and small molecule disturbances.

The potential of this public resource is obvious, but it raises the question: how can researchers outside the consortium take advantage of a large and complex dataset? This and the ever-increasing complexity of data further underscores the need for accessible tools. We are already seeing AI-based analytics tools becoming more mainstream, machine learning (ML) and deep learning (DL) emerging, and talk of more advanced integrations, such as multi-omics, are underway, turning into a new area of ​​research.

Drug discovery sector

Image Credit: paulista/Shutterstock.com

What will the next few years look like for Core Life Analytics? Are there any innovations you are striving towards?

Over the next few years, we hope to tackle other bottlenecks in high-content filtering. One of our ambitions is, in addition to digital data, to move images to the cloud. This will solve many people’s storage problems and allow us to use massively parallel cloud computing for image analysis, dramatically reducing analysis time.

Where can our readers keep up to date with company activities?

They can follow us on LinkedIn or visit our website.

Please provide links to any material that may be relevant to our audience.

On November 15, we will host a webinar: get ready for the JUMP-CP!

More information about the JUMP-CP Consortium can be found on their website.

More information about StratoMineR for high-grade data can be found in our brochure.

About Victor Wang

As CSO, Victor Wong’s responsibilities are to establish and communicate the scientific validity and utility of the research products developed by Core Life Analytics. He interacts with the scientific and customer communities regarding our company’s scientific capabilities and discoveries. He also manages with other CxOs the overall management of the products and the team. Victor Wang

Victor Wong earned his Ph.D. at the University of Toronto. He was a fellow of the Canadian Institutes of Health Research and received several grants during his postdoctoral training at the Burke Institute of Weill Cornell Medicine. His scientific motivation is driven by his disability; he is profoundly deaf and since then his scientific journey has taken him across a number of therapeutic areas, with a focus on target and drug discovery to find new treatments for a number of diseases spanning the metabolism, oncology, neurodegeneration and hearing loss.

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SOPHiA GENETICS partners with Microsoft to accelerate the analysis of multimodal health data https://opendice.net/sophia-genetics-partners-with-microsoft-to-accelerate-the-analysis-of-multimodal-health-data/ Tue, 01 Nov 2022 13:39:00 +0000 https://opendice.net/sophia-genetics-partners-with-microsoft-to-accelerate-the-analysis-of-multimodal-health-data/ Agreement aims to extend and strengthen data-driven medicine through the SOPHiA DDM™ healthcare data analytics platform available with Microsoft Azure GENEVA, November 1, 2022 /PRNewswire/ — SOPHiA GENETICS™ (Nasdaq: SOPH), a cloud-native healthcare software company, is embarking on a multi-year integrated strategic partnership with Microsoft to improve healthcare workflows globally. This investment in the development […]]]>

Agreement aims to extend and strengthen data-driven medicine through the SOPHiA DDM™ healthcare data analytics platform available with Microsoft Azure

GENEVA, November 1, 2022 /PRNewswire/ — SOPHiA GENETICS™ (Nasdaq: SOPH), a cloud-native healthcare software company, is embarking on a multi-year integrated strategic partnership with Microsoft to improve healthcare workflows globally. This investment in the development of next-generation healthcare will lead the way in enabling the curation, development and deployment of multimodal data. As a result, the SOPHiA DDM powered by Microsoft Azure™ The platform is expected to elevate the standard of care for patients, delivering advanced results for precision medicine.

The SOPHiA GENETICS global network breaks down data silos, enabling the democratization of data-driven medicine by connecting institutions that operate diverse multimodal datasets on the SOPHiA DDM™ Platform. Multimodal healthcare datasets can be the largest and most complex to structure, analyze, and archive, and this far-reaching partnership will focus on accelerating results, improving performance, and ultimately, improving medical research by propelling the transition to precision medicine on a global scale.

“With the scale of Microsoft and the power of the SOPHiA DDM™ platform, this partnership will help improve clinical outcomes and make patient care more efficient and personalized,” said Jurgi Camblong, PhD., co- founder and CEO, GENETIC SOPHIA. “SOPHiA GENETICS will help accelerate the transition to a decentralized model of care for hospitals, healthcare providers and biopharma by breaking down data silos and delivering innovations at scale.

“SOPHiA GENETICS’ mission is to democratize data-driven medicine. Microsoft is pleased to support this mission by providing a secure and scalable cloud infrastructure, alongside SOPHiA GENETICS’ advanced artificial intelligence and machine learning tools and technologies that can help generate actionable insights, which can lead to better health outcomes,” said David C. RhewMD, Global Medical Director, Microsoft.

This strategic partnership strengthens the collaboration between SOPHiA GENETICS and Microsoft. SOPHiA GENETICS offers its SOPHiA DDM™ AI and machine learning platform on Azure, leveraging various Azure services that enable greater efficiency and open up opportunities to advance tools to unlock medical data and important genomics. With the addition of the SOPHiA DDM™ platform, providers using Azure will expand their ability to aggregate multimodal data types to extract insights into existing workflows to deliver the best care possible. As one of Microsoft’s chosen partners for precision medicine, SOPHiA GENETICS will help accelerate the transition to a decentralized care model for hospitals, healthcare providers and biopharma, by breaking down data silos and delivering innovations at scale.

SOPHiA GENETICS products are for research use only and should not be used in diagnostic procedures unless otherwise specified. The information in this press release relates to products that may or may not be available in different countries and, where applicable, may or may not have received marketing approval or clearance from a government regulatory body for different indications for use. please contact [email protected] to obtain the appropriate product information for your country of residence.

About SOPHiA GENETICS

SOPHiA GENETICS (Nasdaq: SOPH) is a software company dedicated to establishing the practice of data-driven medicine as the standard of care and for life science research. He is the creator of the SOPHiA DDM™ platform, a cloud-native platform capable of analyzing data and generating insights from complex multimodal datasets and different diagnostic modalities. The SOPHiA DDM™ platform and associated solutions, products and services are currently used by an extensive network of hospitals, laboratories and biopharmaceutical institutions around the world. For more information, visit SOPHiAGENETICS.COM or log on to TwitterLinkedIn, Facebook, and Instagram. Where others see data, we see answers.

SOPHiA GENETICS forward-looking statements:

This press release contains statements that constitute forward-looking statements. All statements other than statements of historical fact contained in this press release, including statements regarding our future operating results and financial condition, business strategy, products and technology, and plans and objectives for direction for future operations, are forward-looking statements. . Forward-looking statements are based on the beliefs and assumptions of our management and on information currently available to our management. These statements are subject to risks and uncertainties, and actual results may differ materially from those expressed or implied by the forward-looking statements due to a variety of factors, including those described in our filings with the Securities and Exchange. United States Commission. No assurance can be given that these future results will be achieved. These forward-looking statements contained in this press release speak only as of the date hereof. We expressly disclaim any obligation or undertaking to update any forward-looking statements contained in this press release to reflect any change in our expectations or any change in events, conditions or circumstances on which such statements are based, unless required to do so. by the rights. No representation or warranty (express or implied) is made as to the accuracy of these forward-looking statements.

SOURCE SOPHiA GENETICS

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Fivetran Introduces Metadata API – Enables End-to-End Data Analytics and Visibility https://opendice.net/fivetran-introduces-metadata-api-enables-end-to-end-data-analytics-and-visibility/ Thu, 27 Oct 2022 06:10:46 +0000 https://opendice.net/fivetran-introduces-metadata-api-enables-end-to-end-data-analytics-and-visibility/ Enterprises can trace the full lineage of data across data catalogs to meet complex compliance requirements and enable global teams to access the right data securely Fivetran, the global leader in modern data integration, has introduced the Fivetran Metadata API which enables “in-flight” tracking of data from source to destination as it moves through pipelines […]]]>

Enterprises can trace the full lineage of data across data catalogs to meet complex compliance requirements and enable global teams to access the right data securely

Fivetran, the global leader in modern data integration, has introduced the Fivetran Metadata API which enables “in-flight” tracking of data from source to destination as it moves through pipelines managed by Fivetran. With this added visibility, customers can integrate governance and observability tools to give data teams more control over who has access to what data. Enabling automated data governance, the Fivetran Metadata API also provides data managers, security teams, and data engineering teams with the visibility needed to know where the data came from, who accessed it, and what changes. occurred in the pipeline.

“Every business knows they need to be data-driven, but traditional data governance has been a barrier with manual processes and reactive policy enforcement. It’s not a scalable approach, especially since data infrastructure turns into thousands of pipelines,” said Vikram Labhe, Vice President and General Manager India at Fivetran. “With the Metadata API, our customers benefit from data governance automations and out-of-the-box data quality workflows so they can proactively identify and act on governance issues before they become a problem. Our automated in-flight approach enables large-scale data access without increasing business risk. »

India’s IT laws impose fines on companies that don’t follow complex rules to protect data privacy. The Fivetran Metadata API helps companies meet compliance requirements, easily integrating into their existing privacy and security strategies while enhancing the value of investments they have made in data catalogs and data management solutions. data quality.

With the Fivetran Metadata API:

  • Data analysts have a deep understanding of the origin of the data and are able to perform impact analysis on it.
  • Data stewards know that end users have access to data that has been securely processed and meets governance requirements.
  • Security and legal teams can perform security audits and ensure that the data being moved complies with organizational policies.
  • Data architects and engineers will soon be able to understand upstream schema changes and ensure downstream processes are kept up to date.

Create an automated data governance experience – Fivetran partners with leading data catalogs

Fivetran is excited to launch better metadata management with four leading data catalog providers: Atlan, data.world, Alation and Collibra. Here are the combined benefits:

  • Information about all data can be consolidated into a single data catalog, for a complete view and a seamless user experience.
  • End-to-end data lineage charts are available for data, even if the data flows through multiple systems and tools.
  • By centralizing governance in a single tool, data stewards can better ensure that policies and processes are applied to data when needed.
  • The ability to source column-level trace data back to its origin helps confirm data quality and builds confidence in data accuracy and safety of use.

“Fivetran’s Metadata API solves a major gap in extracting data from operational systems to modern analytical systems by providing the much-needed context. The availability of the Metadata API will accelerate the development of reliable and secure applications at data-intensive by exposing aspects of lineage, impact analysis, security and privacy,” said Sanjeev Mohan, Director of SanjMo, data and analytics expert and former research vice president at Gartner.

To learn more about Fivetran’s security and governance, visit Fivetran Security or the Fivetran Blog.

For additional images and resources, please visit the Fivetran newsroom.

About Fivetran

Fivetran is the world leader in modern data integration. Our mission is to make access to data as easy and reliable as electricity. Built for the cloud, Fivetran enables data teams to centralize and effortlessly transform data from hundreds of SaaS and on-premises data sources into high-performance cloud destinations. Fast-moving startups from the world’s largest enterprises use Fivetran to accelerate modern analytics and operational efficiency, fueling data-driven business growth. Fivetran is headquartered in Oakland, California, and has offices around the world. For more information, visit fivetran.com.
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International Travel Data and the Power of Big Data Analytics https://opendice.net/international-travel-data-and-the-power-of-big-data-analytics/ Tue, 25 Oct 2022 15:18:30 +0000 https://opendice.net/international-travel-data-and-the-power-of-big-data-analytics/ Image from Pixabay With the advent of big data analytics, there are now multiple ways to create international travel statistics. The ability to analyze travel data and uncover trends allows businesses to make better decisions about their marketing efforts and ultimately helps them find new ways to increase revenue. The global economy is changing, and […]]]>
Image from Pixabay

With the advent of big data analytics, there are now multiple ways to create international travel statistics.

The ability to analyze travel data and uncover trends allows businesses to make better decisions about their marketing efforts and ultimately helps them find new ways to increase revenue.

The global economy is changing, and so are the ways we travel. From new ways to book travel to the power of big data analytics to better predict future trends, we’ll see how our world is changing.

  • Internet and its impact on global travel

The internet is changing the way we travel, both large and small. Booking flights, finding accommodation, checking prices and purchasing; there are more ways than ever to search for the things we need. One way to approach the problem of how to sell the best way to use the internet for your business is to see it as another medium for your business.

There are many reasons why people choose to travel abroad. One of the reasons people choose to internationalize is because of the internet. In recent years, the Internet has allowed travelers to enjoy their trip more than ever before.

We’ve gotten so used to the convenience of being able to search for a flight or hotel room online that we don’t even consider booking offline anymore. And that convenience isn’t just limited to travelers either. Small business owners use online platforms to increase their revenue, hire freelancers, and even manage their employees.

  • Global tourism and the importance of data

The world’s largest travel agency, TUI, uses data to manage its travel business around the world. According to the company, “The ability to forecast demand in real time allows us to respond faster, deliver better services, and maximize our investments in facilities, hotels, and other assets.” In addition to being able to forecast demand, they also use data to predict the likelihood that people will choose to travel to a specific destination. They can also look for correlations between demand and travel patterns. For example, if demand is high in South America, they may send more employees there to ensure the company can meet those demands.

Data is not only a big part of our lives; it is the engine of growth for the tourism industry. Global tourism accounts for approximately 14% of global GDP. It generates over 6.8 million jobs and in 2012 it contributed $3.1 trillion to the global economy. Although the tourism industry is large, its global footprint is still relatively small.

  • Why Big Data is Essential for Destination Marketing

Big Data is important in the world of destination marketing because it allows brands to understand what people like about their destinations. This way they can connect with customers on an emotional level and create relevant offers. So, if you are in the travel industry and planning a trip, using big data would help you connect with your customers based on their interests and preferences.

Businesses can use this information to design more effective campaigns and create the right content for their target customers. Another way is to use it to find out what consumers like in certain destinations and create more appealing products and services. Another way to use big data is to find out what consumers care about and then create products and services that meet their needs.

Big data allows you to know more about your customer. By learning more about your customer, you can develop more relevant products that will make your business more successful. Big Data allows you to analyze and understand trends and data that impact your business. It also helps you find out what your audience wants. This is why big data is important in the destination marketing industry. You can use it to better understand your audience. For example, if you are planning a vacation, big data will help ensure that you have a comfortable hotel room.

  • How Big Data is Changing the Travel Industry

Big data is changing the travel industry in many ways. The big change is that more and more companies are using data and technology to better understand traveler preferences, which helps them create better customer experiences.

“Travel data” encompasses a range of information, from where a traveler is going to where they have been, how long a trip lasts, and which hotels the traveler will be staying at. Travel data is collected using different techniques, including data mining, geofencing and user tracking. Data is collected in real time and used to target marketing messages to potential travellers. This process can help increase conversion rates and ultimately provide the travel agency with a better understanding of their customers.

  • Data and tourism marketing

With tourism becoming an increasingly popular sector of the economy, more and more travel agencies are seeing the potential of marketing with data. In fact, over the past five years, travel agencies have experienced revenue growth of approximately 11% each year. While it is true that many traditional marketing methods are being replaced by digital marketing methods, travel agencies still have a vital role to play in the tourism industry.

Data-driven marketing is about using data and analytics to target your audience. Travel agencies use this method to better understand their audience and how best to target them. For example, travel agencies may collect information on the number of customers who viewed their travel deals on social media platforms. They may also study customers who view their offers on social media and use this information to target new customers with similar interests.

In conclusion, it’s all about getting the most out of every bit of data you can. By using the right technology and tools like Delphix and taking advantage of the best tools, you can analyze data to gain insights and better understand your customers’ behavior and where they spend the most time. The more you know, the better you can serve them and provide them with a better experience.

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CAPITAL: major advance in the analysis of single-cell RNA data https://opendice.net/capital-major-advance-in-the-analysis-of-single-cell-rna-data/ Mon, 24 Oct 2022 02:42:00 +0000 https://opendice.net/capital-major-advance-in-the-analysis-of-single-cell-rna-data/ Researchers at Osaka University have developed a computational tool called CAPITAL that can perform precise comparative analysis of complex single-cell sequencing datasets New developments in high-throughput biological studies mean that genes that are active in a single cell can now be determined. However, analyzing the resulting complex datasets can be challenging. Now a team from […]]]>

Researchers at Osaka University have developed a computational tool called CAPITAL that can perform precise comparative analysis of complex single-cell sequencing datasets

New developments in high-throughput biological studies mean that genes that are active in a single cell can now be determined. However, analyzing the resulting complex datasets can be challenging. Now a team from Osaka University has developed CAPITAL, a new computational tool for comparing complex data sets from single cells.

RNA sequencing provides information about the subset of the entire population of genes that are actively expressed or “turned on”. As technology has advanced, it has become possible to sequence the RNA population of a single cell. This can provide a lot of information about the specific changes in gene expression involved when a large population of mixed cells undergoes dynamic and transient processes, such as differentiation or cell death, because each individual cell can be specifically analyzed rather than all different cells. types being grouped.

CAPITAL is specifically designed to compare complex data sets from single cells undergoing transition processes. These analyzes are carried out by defining a “pseudo-temporal trajectory”, which places the cells along a hypothetical path reflecting their progress in the transition process. These trajectories are not always simple and linear; they can become very complex and branched. In the past, only linear trajectories could be aligned for comparison, but the team’s innovation means that complex branching trajectories can now be aligned and compared precisely and automatically.

After developing the algorithm used for CAPITAL, which implements a method known as tree alignment, they tested it on both synthetic datasets and authentic datasets from cells in bone marrow. The results demonstrated that CAPITAL is statistically more accurate and robust than previous computational algorithms, showing major advances over these methods.

Trajectory comparison is a powerful analysis that can, for example, identify the dynamics of gene expression between different species to provide insight into evolutionary processes. “We have shown in this study that CAPITAL can reveal the existence of different molecular patterns between humans and mice, even when the expression patterns are similar and appear to be conserved,” says lead author Reiichi Sugihara. “This will allow the identification of novel regulators that determine cell fate.” This technology is not limited to this type of data, as lead author Yuki Kato explains: “Our new computational tool can be applied to a wide range of high-throughput data sets, including pseudo data. -temporal, spatial and epigenetic.”

This powerful new technique will allow the global comparison of single-cell trajectories, which could lead to the identification of new disease-associated genes that could not be identified by previous comparative methods. Thus, CAPITAL represents a significant advance in the field of single-cell biology.

Fig. 1

Presentation of CAPITAL: an algorithm for comparing pseudo-temporal trajectories with branches

1 credit

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Figure 2

CAPITAL is statistically better than data integration methods in conserving trajectories across 2,278 pairs of multi-branch synthetic datasets

Credit: 2022 Sugihara et al., Single-Cell Trajectory Tree Alignment with CAPITAL, Nature Communications

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Figure 3

Dynamics of CSF1 gene expression along pseudo-time from hematopoietic stem cell to erythrocyte between human and mouse from bone marrow cell data

Credit: 2022 Sugihara et al., Single-Cell Trajectory Tree Alignment with CAPITAL, Nature Communications

/Public release. This material from the original organization/authors may be ad hoc in nature, edited for clarity, style and length. The views and opinions expressed are those of the author or authors. See in full here.

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Oracle Pushes Cloud as a Service, AI/ML for Data Analytics https://opendice.net/oracle-pushes-cloud-as-a-service-ai-ml-for-data-analytics/ Wed, 19 Oct 2022 13:26:00 +0000 https://opendice.net/oracle-pushes-cloud-as-a-service-ai-ml-for-data-analytics/ Image: Panama/Adobe Stock Making better business decisions faster is a top priority for tech-savvy organizations today, as key announcements from Oracle’s CloudWorld conference show. Oracle’s biggest announcement in the world of edge and cloud computing is Oracle Alloy, a cloud infrastructure platform designed to enable organizations to become cloud providers for their customers. Take a […]]]>
Image: Panama/Adobe Stock

Making better business decisions faster is a top priority for tech-savvy organizations today, as key announcements from Oracle’s CloudWorld conference show. Oracle’s biggest announcement in the world of edge and cloud computing is Oracle Alloy, a cloud infrastructure platform designed to enable organizations to become cloud providers for their customers. Take a look at their other offerings, including the latest Oracle 23c database release, several new distributed cloud offerings, and the updated HeatWave Lakehouse MySQL database tool.

Jump to:

Oracle Alloy

Partner organizations can use this cloud infrastructure platform in their own data centers, an attractive option that allows flexibility in terms of regulatory requirements. It also allows organizations to extend the partnerships they may already have with Oracle Cloud Infrastructure to the public sector or other industries that may want to operate clouds independently, turning them into middle-of-the-road cloud providers.

SEE: Recruitment Kit: Cloud Engineer (TechRepublic Premium)

“Customers are increasingly looking to run their workloads in specific locations and to run those workloads in the cloud of their choice,” Oracle found.

The Alloy Platform offers the same 100 infrastructure and platform services accessible in OCI’s public cloud. From here, customers can add their own branding, SDKs, documentation, pricing, account types, and discount schedules. Alloy is open to customers bringing specific hardware appliances into the ecosystem and using what works best for them locally to bring the cloud supported by Oracle.

Oracle Cloud Infrastructure developers have extended Oracle Distributed Cloud to include more development services. Specifically, the extension adds services for building cloud-native apps, artificial intelligence data services, low-code development and more. Easing the transition to cloud-native services includes Virtual Nodes functionality for Oracle Container Engine for Kubernetes and Container Instances service.

Containers and Kubernetes are both commonly talked about in the same breath as cloud computing today. Oracle hopes to reduce the complexity and management overhead needed for developers to run them. Virtual Nodes provide granular elasticity at the pod level with resource-consumed pricing per pod without having to manage as much infrastructure.

MySQL HeatWave Lakehouse

Next up is an update to Oracle’s database cloud service for MySQL, HeatWave Lakehouse. HeatWave is an enhancement to an analytics database service for MySQL, to improve the speed of transactional and analytics services. This memory cluster processes and queries hundreds of terabytes of data in the object store in a variety of file formats. Clients using it come from the marketing analytics, automotive, telecommunications, high-tech and other industries.

MySQL HeatWave Lakehouse was created in coordination with AMD and as such is optimized for Oracle cloud instances powered by AMD EPYC. Data size has increased up to 400 TB of data, and the HeatWave cluster scales up to 512 nodes. It’s also ready to work in multiple clouds, including OCI, AWS, and now Microsoft Azure.

23c beta database

Oracle Database 23c, the latest version of Oracle’s converged database, is now in beta. The latest version focuses on simplifying the development of applications in JSON, Graph or microservices. It also includes JSON Relational Duality to resolve a common mismatch between how applications represent data and how relational databases store it.

It comes with a variety of upgrades on this theme of simplification, including JSON relational duality, JavaScript stored procedures, analysis of operational data property graphs, automated transaction management of distributed microservices, views automatic materializations, real-time SQL plan management, True Cache, ML-enhanced prediction of data statistics to optimize SQL execution and native replication of database fragments.

Oracle APEX 22.2 is now also in preview as part of the beta release. APEX’s Progressive Web App enhancements improve low-code app development by working in a virtually native mobile user experience.

Two up-to-date recovery services ensure that data will be available even in an emergency, such as catastrophic weather, which could lead to loss of power or physical damage. Oracle Database Zero Data Loss Autonomous Recovery Service is a recovery service for other Oracle services. The OCI Full Stack Disaster Recovery service provides customers with an overview of their recovery process, viewing the entire technology stack from the OCI console.

Data Analysis Services

Oracle has released several new product updates in the area of ​​data and analytics solutions. They have been developed in a world where growing awareness of the skills gap has led to a design philosophy that favors moving away from a heavy reliance on IT, remembering that people should always be aware at all stages of the process.

In particular, Oracle offers advanced composite visualizations as a way to solve the problem of interpreting data that is too complicated or takes too long. Artificial intelligence and machine learning are becoming the eyes and ears of industry as Oracle turns them to Analytics Cloud and other Oracle Cloud Infrastructure cognitive services like AI Vision, all in dashboards in one look.

Along with a slew of Oracle Fusion Analytics products, several new Oracle Analytics Cloud features were announced this week, stemming from the roots of AI/ML. A semantic modeler creates a more readable layer between business users and the complexity of physical data sources in a centralized semantic model.

Business users can also take advantage of advanced composite visualizations to move metrics in charts and analyze data patterns and signals. Another one-click feature provides proactive automated insights for building visualizations, powered by Oracle Analytics Cloud.

Autonomous Data Warehouse in particular comes with a new coat of paint. It can now take advantage of a new Excel add-in and has a new comprehensive and integrated data integration tool with Transforms. The GoldenGate OCI flow analysis tool has new capabilities to discover and test outliers and anomalies, apply insights from ML models, and help decide the next best course of action.

Overall, visibility, ease of use, and cloud connectivity emerged as themes for Oracle’s recent announcements.

Find more information on Oracle cloud products and comparisons between Oracle HR software and Workday or Oracle ERP software and SAP.

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Unlocking the Integral Role of Data Analytics for Business https://opendice.net/unlocking-the-integral-role-of-data-analytics-for-business/ Tue, 18 Oct 2022 21:38:15 +0000 https://opendice.net/unlocking-the-integral-role-of-data-analytics-for-business/ Data analysis is indeed the key to uncovering major insights that are hidden among the vast array of data that companies collect. This information can help businesses improve their operations. An organization can benefit from data analytics in a variety of ways, including the ability to recognize and mitigate potential business risks, as well as […]]]>

Data analysis is indeed the key to uncovering major insights that are hidden among the vast array of data that companies collect. This information can help businesses improve their operations.

An organization can benefit from data analytics in a variety of ways, including the ability to recognize and mitigate potential business risks, as well as personalize marketing messages for individual customers.

Personalization of the consumer experience

Companies collect customer information from a wide range of sources, including physical stores, online marketplaces, and social media.

Using data analytics to create comprehensive customer insights from this data allows businesses to gain insight into customers and provide a more personalized experience.

To illustrate, think of a clothing store that sells items both online and in physical locations. The Company may combine its sales data with information from its social media profiles to develop social media marketing specifically aimed at encouraging online purchases of products in which customers have already expressed an interest.

By applying models from the field of behavioral analysis to customer data, companies can further improve the quality of their service to end users.

Informed decisions

An organization’s financial losses can be mitigated with the help of data analytics, which can also help guide business decisions.

Prescriptive and predictive analytics help businesses prepare for potential outcomes in response to market changes.

To predict how customers would react to a price drop or new product offering, companies can use simulation tools. The validation of the hypotheses produced by such models can be done by A/B testing variations in product offerings.

Once new product sales data has been collected, companies can use data analytics methods to assess the effectiveness of adjustments and visualize the results to better inform implementation decisions at the time. company wide.

Simplified functions

Data analytics can help businesses increase productivity. If you collect and analyze supply chain data, you can uncover the source of manufacturing bottlenecks and delays and avoid them in the future.

If a company’s demand forecast shows that one of its suppliers will not be able to meet seasonal demands, such as those seen during the holidays, then the company can seek out a new supplier to work with.

Data analysis can help companies determine how much of each service to keep in light of factors such as seasonality, holiday periods and secular trends.

Appropriate management of risks and setbacks

There are always potential dangers when doing business. This includes theft from customers or staff, unpaid bills, unsafe workplaces and legal issues.

Data analytics can help a business analyze risks and take precautions.

That said, the use of trading analytics sites like Quantum AI has helped traders with lucrative financial management tips under the banner of its effective data analytics mechanisms.

Increased protection

All businesses face the perils of unsecured data at some point. Organizations can use data analytics to determine the root causes of past data breaches through the examination and visualization of required data.

Especially in load-based attacks like scattered denial of service (DDoS), attacks typically involve anomalous access behavior.

These models can be configured to run indefinitely, with added monitoring and notification mechanisms to identify and report anomalies for immediate action by security professionals.

The essential

Data analytics is indeed the key to unlocking the useful insights locked away in the vast trove of data that companies collect.

The use of data analytics can benefit a business in a number of ways, such as allowing the business to customize its marketing efforts for each particular consumer and mitigating the impact of previously unknown dangers.

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