Disruptive Data Science Series: Transforming Your Company into a Data Science...EMC
Big Data is the latest technology wave impacting C-Level executives across all areas of business, but amid the hype, there remains confusion about what it all means. The name emphasizes the exponential growth of data volumes worldwide (collectively, 2.5 Exabytes/ day in the latest estimate I saw from IDC), but more nuanced definitions of Big Data incorporate the following key tenets: diversification, low latency, and ubiquity. In the current developmental-phase of Big Data, CIOs are investing in platforms to “manage” Big Data.
Disruptive Data Science Series: Transforming Your Company into a Data Science...EMC
Big Data is the latest technology wave impacting C-Level executives across all areas of business, but amid the hype, there remains confusion about what it all means. The name emphasizes the exponential growth of data volumes worldwide (collectively, 2.5 Exabytes/ day in the latest estimate I saw from IDC), but more nuanced definitions of Big Data incorporate the following key tenets: diversification, low latency, and ubiquity. In the current developmental-phase of Big Data, CIOs are investing in platforms to “manage” Big Data.
How 3 trends are shaping analytics and data management Abhishek Sood
Explore how 3 current trends are shaping modern data environments and learn about the impact of non-relational databases, big data, cloud data integration, self-service analytics, and more.
Virtual Data Steward: Data Management 3.0CrowdFlower
Every company that is serious about data governance needs data stewards. Data stewards connect business information requirements and processes with information technology capabilities. This function is essential to bridging data management policies and standards to day-to-day operational practices.
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Dana Gardner
Transcript of a discussion on how HTI Labs in London provides the means and governance with their Schematiq tool to bring critical data to the interface that users want most.
This talk is an introduction to Data Science. It explains Data Science from two perspectives - as a profession and as a descipline. While covering the benefits of Data Science for business, It explaints how to get started for embracing data science in business.
The use of new forms of data is not an evolution. Instead, powering big data supply chains, and innovating through new forms of analytics, is a step change.
New forms of data do not fit traditional architectures. Traditional supply chains were architected to use structured data with software using relational databases. The big data era will make many of the investments from the last decade obsolete.
Big data offers the opportunity to redefine supply chain processes from the outside-in (from the channel back) and define the customer-centric supply chain. This is in stark contrast to the inflexible IT investments installed over the last decade to respond inside-out based on order shipments. These traditional investments in Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and traditional Business Intelligence (BI) for reporting, improved the supply chain response, but did not allow the organization to sense, shape or orchestrate outside-in. New forms of data (e.g., images, social data, sensor transmission, input from global positioning systems (GPS), the Internet of Things, and unstructured text from email, blogs and ratings and reviews) offer new opportunities. They also require new techniques and technologies.
Big data offers new opportunities for the corporation to listen, test and learn, and respond faster. In this study, companies see the greatest opportunity to use big data for “demand” (to better know the customer and improve the response); however, actual investments are in “supply” not “demand.” Respondents view supply-centric projects like product traceability (involving product serialization and traceability), supply chain visibility and temperature controlled handling as important.
Is big data a problem or a new market opportunity? Like the respondents of this survey, we believe that big data represents an opportunity for all. In the study, one-fourth of respondents currently have a big data initiative. However, interest is growing. Sixty-five percent have or plan to have a big data initiative in the future. Despite the hype, and the intensity of marketing rhetoric in the market, in our year-over-year studies on big data we see very little change in activity.
Despite the fact that the IT group is more likely to see big data as a problem, 49% of those with a big data initiative report that it is headed by an IT leader.
Big data represents a new opportunity, but seizing it requires a new form of leadership. It can ignite new business models and drive channel opportunities. However, it cannot be big data for big data itself. Instead, the initiatives need to be aligned to business objectives with a focus on small and iterative projects. It requires innovation. To move forward, companies need to embrace new technologies and redesign processes. It is not the case of stuffing new forms of data into old processes.
How 3 trends are shaping analytics and data management Abhishek Sood
Explore how 3 current trends are shaping modern data environments and learn about the impact of non-relational databases, big data, cloud data integration, self-service analytics, and more.
Virtual Data Steward: Data Management 3.0CrowdFlower
Every company that is serious about data governance needs data stewards. Data stewards connect business information requirements and processes with information technology capabilities. This function is essential to bridging data management policies and standards to day-to-day operational practices.
Democratizing Advanced Analytics Propels Instant Analysis Results to the Ubiq...Dana Gardner
Transcript of a discussion on how HTI Labs in London provides the means and governance with their Schematiq tool to bring critical data to the interface that users want most.
This talk is an introduction to Data Science. It explains Data Science from two perspectives - as a profession and as a descipline. While covering the benefits of Data Science for business, It explaints how to get started for embracing data science in business.
The use of new forms of data is not an evolution. Instead, powering big data supply chains, and innovating through new forms of analytics, is a step change.
New forms of data do not fit traditional architectures. Traditional supply chains were architected to use structured data with software using relational databases. The big data era will make many of the investments from the last decade obsolete.
Big data offers the opportunity to redefine supply chain processes from the outside-in (from the channel back) and define the customer-centric supply chain. This is in stark contrast to the inflexible IT investments installed over the last decade to respond inside-out based on order shipments. These traditional investments in Enterprise Resource Planning (ERP), Advanced Planning Systems (APS) and traditional Business Intelligence (BI) for reporting, improved the supply chain response, but did not allow the organization to sense, shape or orchestrate outside-in. New forms of data (e.g., images, social data, sensor transmission, input from global positioning systems (GPS), the Internet of Things, and unstructured text from email, blogs and ratings and reviews) offer new opportunities. They also require new techniques and technologies.
Big data offers new opportunities for the corporation to listen, test and learn, and respond faster. In this study, companies see the greatest opportunity to use big data for “demand” (to better know the customer and improve the response); however, actual investments are in “supply” not “demand.” Respondents view supply-centric projects like product traceability (involving product serialization and traceability), supply chain visibility and temperature controlled handling as important.
Is big data a problem or a new market opportunity? Like the respondents of this survey, we believe that big data represents an opportunity for all. In the study, one-fourth of respondents currently have a big data initiative. However, interest is growing. Sixty-five percent have or plan to have a big data initiative in the future. Despite the hype, and the intensity of marketing rhetoric in the market, in our year-over-year studies on big data we see very little change in activity.
Despite the fact that the IT group is more likely to see big data as a problem, 49% of those with a big data initiative report that it is headed by an IT leader.
Big data represents a new opportunity, but seizing it requires a new form of leadership. It can ignite new business models and drive channel opportunities. However, it cannot be big data for big data itself. Instead, the initiatives need to be aligned to business objectives with a focus on small and iterative projects. It requires innovation. To move forward, companies need to embrace new technologies and redesign processes. It is not the case of stuffing new forms of data into old processes.
As we enter the digital economy, it becomes increasingly transparent that the information and data ecosphere will continue to be a complex environment for the foreseeable future, with information being provided from a variety of internal and external sources in the form of files, messages, queries and streams. It would be foolish for any organization to place their bets on any one platform to be their platform of choice because it is incongruent to the thought patterns of the consumers, suppliers, regulators, partners and financiers who will participate in their information ecosphere through data feeds, information requests and a host of other interfaces.
Rather, there is a role of each of these platforms which serve as the conduit for data and the transformation of data into information aligned with the value propositions of the organization. This writing is focused on the big data platform because there are some unique characteristics of the big data environment that require an approach different than many of the legacy environments that exist in organizations. Furthermore, while big data is the one environment that is new and requires these special handling characteristics, there will be future platforms with the same requirements as big data requires today, and hopefully lessons learned will be left to not revisit each of the challenges as the next transformational information ecosphere is made available.
Figure 1 The Fourth Industrial Revolution, World Economic Forum, InfoSight Partners, 2016
This time is different, in that information is the catalyst to achieving value and the platform ideally suited to house information not optimal for storage in the form of rows and columns is the big data environment. Understanding which information is delivered with intended consequences and having the management prowess to tune information shared with customers, prospects, suppliers, partners, regulators and financiers is critical for the digital economy. Additionally, it is specific to understand the challenges each platform housing information bring to the equation. This writing will focus on big data.
An efficient data science team is crucial for deriving value from the humongous data a business collect. Learn how the data science team can help in this regard.
In this document, the five disruptive trends shaping the corporate IT landscape today are layed out. Out of the five, Big Data has the biggest potential to generate new sustainable competitive advantages. But the benefits will remain out of reach of many organizations as they struggle to adopt the technology, develop new capabilities, and manage the cultural change associated with the use of big data. This document offers a pragmatic approach to generating business value.
The analytics market is abuzz where professionals from various disciplines and background are leveraging data in their daily activities to get maximum insights and help a business to grow.
The financial volatility unleashed by the
pandemic has opened the doors of opportunity
for Banking and Financial Services (BFS)
companies. Technology-driven digital
transformation is expected to drive further shifts
in this new normal.
The industry will witness the adoption of
innovative technologies driven by emerging
trends. BFS organizations will increasingly
undertake digital transformation to broaden
their capabilities, and maturing FinTechs will
forge partnerships that drive disruptive growth
and customer-focused innovation.
Here, we explore some trends that will shape
the future of the BFS industry
The most prevalent trend in today’s
financial services industry is the shift to
digital, specifically mobile and online
banking. In the era of unprecedented
convenience and speed, consumers don’t
want to trek to a physical bank branch to
handle their transactions. While on the one
hand, banks are releasing new features to
attract more customers and retain the
existing ones, on the other hand, startups
and neo banks with disruptive banking
technologies are breaking into the scene.
The use of Artificial Intelligence (AI) in the
banking industry can revolutionize the way
banks operate and provide services to
their customers, improving eciency,
productivity, and customer experience.
In the age of disruption, manufacturers need to
constantly find innovative ways to overcome challenges
like data sitting in silos, downtime (which could be
prevented), rigid production and labor shortage issues.
Companies need to listen to their operators and
technicians and enable them to have a say in the
day-to-day processes. Issues like being unable to find a
product/part on the floor lead to unnecessary delays,
miscommunication, and dissatisfaction among workers
The banking, financial services, and insurance (BFSI)
sector has been at the forefront of adopting AI and
machine learning technologies. AI has enabled these
industries to automate processes, reduce costs, and
improve the customer experience. With the advent of
digitization and the increasing amount of data available,
banking, financial services, and insurance companies have
been leaders in using AI and machine learning.
Metaverse has become ae buzzword in the tech industry. Not a single day goes by without a mention of it
in the media, especially around investments, startups building components, new platforms being
announced and large companies entering this world of digital engagement. There is undeniably a huge momentum of an almost real 3D virtual world, and the clarion call was perhaps Facebook rebranding itself
as Meta which will perhaps be remembered as a red letter moment in the evolution of the Metaverse.
Content is one of the most commonly consumed resources in online marketplace. Still,
most organizations struggle to effectively monetize it. Inability to implement viable
and scalable monetization methods not only keeps organizations from discovering
growth opportunities, but can also lead to poor customer experiences.
Digitalization has transformed the way business’s function. With the evolution of technologies, attackers are also evolving. They are finding innovative and more invasive ways to attack organizations. Due to this, the organization's security operations center (SOC) is expected to be
more agile and dynamic in detecting and responding to attacks. Most organizations' security operations and incident response teams are overworked due to high volumes of security threats and alerts that they need to manage every day.
Cloud technology is no longer a new player in the market,
but it’s a mature and integral part of the IT landscape and a
key parameter in driving business growth. It is an
indispensable topic among CXOs. A research by Fraedon has
found that almost half of the banks find their legacy
systems to be the biggest hindrance in their growth.
Client is the leader in work orchestration and observability. Software platform helps enterprises more effectively plan, orchestrate and audit the human and automated activities that drive critical events, such as technology releases, resilience testing, operational readiness and major incident recovery.
A Robust Privileged Access Management (PAM) forms the
cornerstone of an enterprise cybersecurity strategy, providing greater visibility and audibility of an organization's
overall credentials and privileges.
The global disruption due to the pandemic has massively impacted organizations and the way they function.
Organizations are shifting towards a virtual environment by adopting cloud and automation to support,
monitor, and deploy exceptional service to their end-users. But how to keep the end-users connected to the
digital workplace securely during disruption is a big challenge
Let us understand some of the infrastructural and
security challenges that every organization faces today
before delving into the concept of securing the cloud
data lake platform. Though Data lakes provide scalability,
agility, and cost-effective features, it possesses a unique
infrastructure and security challenges.
European government in 2016 adopted General Data Protection Regulation (GDPR) and was
put into effect on May 25, 2018, replacing the 1995’s Data Protection Directive to protect the
personal information of EU citizens. GDPR aims to govern personal data processing and ensure
processing is fair and lawful. It is also designed to emphasize the fundamental right to privacy.
Aure Bastion is a PaaS solution for your remote desktop which is more secure than the
jump server. It comes with web-based login, and never expose VM public IP to the
internet. This service will work seamlessly on your environment using VM’s private IP
address within your Vnet. Highly secure and trustable.
The Retail industry today is dealing with the concerning challenge of rising costs of transportation,
driven by a shortage of trucks and truck drivers, availability of raw material and unprecedented
demand spikes across categories. Retailers like Bed Bath & Beyond have recently warned investors
about the impact of rising freight costs on earnings. As overall freight costs can constitute up to
10% of total expenditure, efficiency in freight invoice management is critical to managing
transportation budgets
The freight ecosystem is vast and complex with many interconnected functions starting from sourcing, manufacturing to bringing products to the consumer. Any organization dealing with
movement or purchase of freight (goods) needs a control mechanism to ensure accuracy of dealing with freight invoices received from carriers.
Tool Integration is an effective technique of integrating tools of the same or different classes to build a robust tool framework to support various business operations.
The Retail industry today is dealing with the concerning challenge of rising costs of transportation,
driven by a shortage of trucks and truck drivers, availability of raw material and unprecedented
demand spikes across categories. Retailers like Bed Bath & Beyond have recently warned investors
about the impact of rising freight costs on earnings. As overall freight costs can constitute up to
10% of total expenditure, efficiency in freight invoice management is critical to managing
transportation budgets.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.