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Your access to this site was blocked by Wordfence, a security provider, who protects sites from malicious activity. If you believe Wordfence should be allowing you access to this site, please let them know using the steps below so they can investigate why this is happening. Mc Gill professor Jackie Cheung to act as academic advisor TORONTO, November 21, 2017 - Continuing its investment in the Canadian artificial intelligence (AI) ecosystem, Borealis AI, an RBC Institute for Research, today announced that it will open a lab in Montreal, one of Canada’s most prominent AI hubs. Borealis AI has partnered with Mc Gill University Professor, Jackie Cheung, as academic advisor for the lab and will work closely with the Montreal Institute for Learning Algorithms (MILA). The team anticipates opening the doors of the new location early in the new year. “Montreal has emerged as a global centre for research in artificial intelligence and I’m excited to be participating in this community,” said Dr. Foteini Agrafioti, head, Borealis AI and chief science officer, RBC. “We’re committed to helping advance the field through the creation of intellectual property and look forward to providing new opportunities for the enormous talent already doing exceptional research in the region.” Professor Cheung is an expert in the field of natural language processing (NLP). NLP, which is the computer’s ability to understand human language, is considered one of the key focus areas of AI research. Its applications to financial services and other industries have the potential for ground-breaking solutions in areas of impact, like the analysis of unstructured text that is prevalent in public and RBC proprietary datasets. Montreal has emerged globally as an AI powerhouse, buoyed by research institutions like the MILA and a rich AI startup ecosystem. Borealis AI will collaborate closely with MILA and Professor Yoshua Bengio, and continue to grow its research partnerships with Mc Gill University and the Université de Montréal. “The MILA is delighted to see a major Canadian business investing in AI research, particularly in long-term difficult questions, and opening a lab in Montreal,” said AI pioneer and head of MILA, Professor Yoshua Bengio. “The collaborations this will bring are not just between MILA and RBC, but also involve other actors in the ecosystem, which is important for the country’s ability to compete internationally. There are plenty of difficult AI research questions of interest to RBC which can have major impact on many sectors of the economy, so this goes well beyond the banking sector.” RBC was also announced today as a partner of the Creative Destruction Lab Montreal (CDL-Montreal). The result of a partnership between HEC Montréal and the University of Toronto’s Rotman School of Management, CDL-Montreal is the city’s first world-class startup support program focused on capitalizing its expertise in AI. About Borealis AI Borealis AI, an RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, with labs in Toronto and Edmonton, Borealis AI supports open academic collaborations and teams up with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, the machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning and unsupervised learning to solve ground-breaking problems in diverse fields. About RBC Royal Bank of Canada is Canada’s largest bank, and one of the largest banks in the world, based on market capitalization. We are one of North America’s leading diversified financial services companies, and provide personal and commercial banking, wealth management, insurance, investor services and capital markets products and services on a global basis. For more information, please visit ‎ RBC helps communities prosper, supporting a broad range of community initiatives through donations, community investments and employee volunteer activities. We have approximately 81,000 full- and part-time employees who serve more than 16 million personal, business, public sector and institutional clients through offices in Canada, the U. For more information please see: com/community-sustainability/. Rbc business intelligence centre rbc guy concordia The COVID-19 outbreak has deeply impacted the lives of many Canadians and their businesses. RBC is committed to providing financial relief for business clients who have experienced financial hardship as a result of the COVID-19 outbreak. View Details Aug 24, 2012 We at RBC Insurance ® are pleased to announce some exciting changes to the RBC Insurance Business Intelligence Centre, effective immediately. Read more about it. Or contact your RBC Insurance regional sales consultant at 1-866-235-4332 for more information. The Retail group has just sent me another quick win request, stated Michael Eubanks, director of marketing information technology (IT), as he walked into his meeting with Andy Wnek, chief information officer (CIO) of Canadian Tire Corporation (CTC). Thats the second one this week, and I have heard whispers about more. Dealing with these quick wins is going to make it difficult to redevelop the business intelligence (BI) infrastructure. Thats where the real return on investment (ROI) is. Over the last year, the IT group at CTC had promoted a strategic initiative to deliver real business value from business intelligence (BI) over the next three years. A massive change effort involving infrastructure, organizational structure and business processes across most of the business would be required. Nevertheless, the plane was still in flight and current needs could not be completely ignored. As the door swung closed on their meeting, Wnek and Eubanks sat down to discuss how they might keep the plane in the air while rebuilding the engines. In 1922, John and Alfred Billes, two brothers, opened a garage and auto parts store in Toronto, Canada. By 2003, their enterprise had grown into CTC, a network of businesses including retail, financial services and petroleum operations. More than 45,000 individuals worked at CTC operations across Canada in more than 1,000 stores and gas bars. CTC businesses were divided into five main groups: Corporately, CTC had completed a strategic plan in late 2002 that stated a clear corporate goal to become a top quartile performer in our market sector as measured by total return to shareholders. This strategic goal was to be accomplished through four strategic imperatives: This new CTC strategic plan guided the development of a CTC IT strategy in February 2003, an effort led by senior vice president and CIO Wnek, to complete the first IT strategy document in several years. As CIO, Wnek was responsible for overseeing the information systems (IS) of the entire enterprise, but not within the associate dealers stores. The BI initiative, while important to the organization overall, was primarily associated with CTR, and it represented one of many IS initiatives competing for CTC support and funding based on the new 2003 IT Strategy 2003. Figure 1 provides an organizational chart of the senior management at CTC and CTR. The Web of businesses comprising CTC was accompanied by a highly complex technical architecture (see Figure 2 for an overview of their organization). A recent enterprise technology review revealed a multitude of hardware, software, operating systems, network services, development tools and applications being utilized across the business. For example, CTR ran IBM AS/400 systems at the store level with point-of-sale (POS) systems and servers that networked to IBM mainframe systems at the CTR data centre. These systems were funded 50 per cent by CTR and were supported by the retail systems group at CTC. The systems at Marks Work Wearhouse still remained entirely separate from the rest of the CTC infrastructure. CTFS in Welland operated on IBM RS6000 with Intel-based workstations. Part Source and CTP relayed transactions directly into the corporate network from their POS systems. In fact, the CTC IT group supported, operated and managed over 100 different mainframe, server and desktop development and integration tools, 10 different hardware platforms, 14 operating systems, seven database management systems and over 450 different production applications and desktop-based applications and tools. Substantial proportions of the hardware, operating systems, network services, data services and development and integration tools were identified as niche (exceptions to current standards) and sunset (to be retired) technologies that needed to be addressed in order to meet the objective of bringing IT spending as a percentage of sales under industry benchmarks of about two per cent. Currently, CTCs IT spending, when measured by accounting for all IT expenditures (including assets and resources expended on IT in other areas), was around this benchmark. The CTC IT strategy document concluded that IS at CTC had evolved into a highly complex and costly environment that offered substantial opportunities for consolidation, simplification, integration and cost-cutting. The results of several IT reviews carried about by consulting firms over the last seven years supported this conclusion. The results highlighted several themes faced by the IT group: In spite of these challenges, IT had delivered several key initiatives in the past few years, including the development of a demand forecasting and replenishment system, Y2K upgrades, the development of Customer Linka supply chain management system. To build on their strengths and the recently developed business strategy, IT Strategy 2003 laid out a strategic vision to be an agile IT team, aligned to business priorities, operating a simpler technical environment with the appropriate standardized processes. Consistent with this vision, three strategic IT imperatives were identified: Four programs were developed to enact the IT vision for the period of 2003 to 2005. The first program was to implement a CIO governance council that would meet quarterly and assume responsibility for developing enterprise standards, monitoring IT spending, undertaking annual IT planning, monitoring the IT strategy and providing opportunities for sharing and collaborating across the enterprise to realize synergies. The second program, organizational and people capabilities, specified key capabilities and services the IT group would need to be able to offer to the organization. Business-consulting, solutions integration, end-user services and support, platform operations and management, and enterprise IT planning and architecture were just some of the capabilities outlined in the IT strategy document. The third program, process improvements, included coordinating an annual IT strategy planning process based on the corporate strategic planning cycle, the development of an opportunity management process that would standardize and regulate the identification, analysis and approval of IT project requests and a monthly IT scorecard reporting on key performance indicators including IT spending as a percentage of sales. The final program was entitled technological direction, and it laid the foundation for re-architecting the organization. To support the IT imperatives outlined above, this program identified five areas for attention: business intelligence and data management, application deployment, integration and messaging, standardization and simplification, and security deployment. Business intelligence and data management activities were identified as high priorities. Consequently, BI quick win projects were prioritized first with development and implementation of a BI strategy and structure to follow over the life of the IT strategic plan. Historically, retail organizations have invested significantly less in information technology than other industries (two per cent of revenue compared with about eight per cent of revenue across other industries). This spending has focused mainly on POS and supply chain management systems. One of the important exceptions to this rule is Wal-Mart. However, due to increasing competition, retailers have turned to BI to improve sales and better serve customers. A recent Forrester Research report indicated that IT executives at 286 North American companies with over $1 billion in sales intended to make business intelligence analytics their second largest IT investment after their Web portal investments.2 BI is the consolidation and analysis of internal data (e.g., transactional POS data) and/or external data (e.g., purchased consumer demographics) for the purpose of effective decision making. Assembling and merging data from various sources is a complex task, and analysis requires the use of highly sophisticated skills. At the core of all BI initiatives is a data warehouse to hold the data and analytics software. The data warehouse stores data from operational systems in the organization (e.g., inventory, POS, accounting, marketing, etc.) and restructures it to enable queries and models to extract decision support reports. With no clear dominant players in the business intelligence market place, many niche players have emerged to serve data warehouse and BI analytics marketsan industry that is expected to grow from US$30 billion to US$75 billion by 2005 in North America alone.3 Figure 3 provides partial information on players in this marketplace. The supply side of the BI marketplace has been characterized by a proliferation of specialty suppliers rather than dominated by a few major players. It has grown through the evolution of various software products and tools offered as standalone products or as part of other product offerings such as ERP systems and data warehouses. The result is that any given organization using BI may be managing and maintaining a half dozen (or more) BI packages, depending on the needs of the end-user groups.1 However, industry watchdogs are predicting consolidation in the BI marketplace around a few high-profile players offering end-to-end BI solutions in the four dominant tool areas: enterprise reporting, ad hoc query and analysis, online analytical processing (OLAP) servers, and analytic dashboards. The recent acquisitions of Crystal Decisions by Business Objects for US$820 million and of Brio Software by Hyperion for US$142 million (during the summer of 2003) provide some evidence of this, although, currently, it is difficult for end-to-end providers to compete with the functionality and capability of discrete specialty providers. This naturally makes it challenging for organizations selecting BI products and tools. BI software is provided by a range of organizations: For example, in order to improve profit and customer service, Hudsons Bay Company (HBC), a major Canadian department store chain, is currently in the process of a multi-year effort to upgrade its IS. Two major data warehouses (one for department store operations and one for discount store operations) have been merged into a single data warehouse enabling executives, store managers and business analysts access and interpret data about store sales, category sales, financial performance and suppliers. Ace Hardware (American hardware retailer similar to CTR in that stores dealer-owned) launched a BI initiative with its 5,000 stores whereby store owners and Ace executives could view and analyse information to aid in category management and promotion decisions. With over 65,000 products from 3,000 vendors, these activities would be impossible for a single store to undertake. A price-setting model has been particularly effective in allowing Ace Hardware store owners to see the implications of setting prices above or below those recommended by head office. While the current application focuses mainly on analysing historical trends, Ace is also developing an application to use and view real-time POS data in real time to see the status of pricing, product and promotion decisions. Numerous other examples of the effective application of BI in the retail industry have also been observed. Despite the benefits from BI and data warehousing investments, implementation of these projects consumed huge organizational resources and was difficult. An IDC report revealed many challenges associated with the iterative nature of over 400 BI implementations reported by over 1,300 respondents. Importantly, the study findings indicated that 35 per cent of all BI implementations were unsuccessful, 35 per cent were adequate and 30 per cent were described as successful: the larger the organization and the more complex the BI implementation, then the lower the likelihood of launching BI successfully, including being on time and on budget. These organizations also prioritized the 10 biggest challenges to achieving success in implementing business intelligence, in descending order: budget constraints, data quality, understanding and managing user expectations, culture change, time required to implement, data integration, education and training, ROI justification, business rules analysis, and management sponsorship. However, two groups of respondents reported different priorities for these challenges. IT managers more frequently mentioned data quality and cultural change as their biggest hurdles. Business managers placed higher priority on education and training for end-users. The study concluded that BI initiatives were iterative projects whereby user expectations and training needs expanded as they gained access to and experience with analysing data. Additionally, variation in the viewpoints of IT and business managers could be pressure points for implementation. Given that most organizations expect their data warehouses and BI investments to continue to grow, these variations in opinions, especially with respect to data quality and end-user training and education, pointed to important areas of BI project management. BI analytics started at CTC in 1994 with the development of the information warehouse (IW), which was implemented by the CTC IT group at the request and funding of CTR. Around that time, the CTC chief executive officer (CEO) began trying to change CTRs image and role from that of a wholesaler to that of a retailer. This led to the realization that more data was required in order to begin analysing data like a retailergoing beyond the store level to examine product, store and margin trends. To facilitate this new logic, the IT group built the IW into which they extracted, transformed and loaded data from a variety of sources, including POS data downloaded from the stores. At that time, Wnek was chief financial officer (CFO) for CTR. His efforts to provide better information for business decision-making led to the creation of retail analytics in the CTR finance group. This ultimately led to a separate departmentthe Finance Retail Analytics Group (FRAG)that performed the bulk of the analysis and prepared reports for the various marketing departments at CTR. Between 19, the IW grew dramatically as more educated end-users in CTR Marketing and analysis within FRAG demanded more data and CPU time to conduct analysis to support business decisions. During this time period, BI efforts fragmenteda situation that persisted and then accelerated from 1998 onwards. The IT group gradually took on a more technical focus for the IW, focusing on loading data and transforming it into more and more summary tables to balance the need for CPU time for user queries against capacity constraints. The goal of summary tables was to cut down on the duplication of queries. During this period, due to a lack of resources which were being used for other projects), the IW was evolving on old infrastructure and a poorly defined data model. Further, a lack of standard data definitions meant that several versions of the truth could be extracted from the IW; depending on the way you defined it, you could end up with six different numbers for inventory levels. Also, some data was just simply not availablea marketing analyst in the sports segment for instance, could not evaluate the results of a weekly promotional effort on golf clubs nor evaluate the performance of various brands against each other e.g., how Titleist performed against Nike products). In its current state, the data model in the IW did not reflect the data requirements of the business. Throughout CTC, user groups gradually undertook more responsibility for IW data management activities so they could perform their own analytic tasks. User groups developed applications and hired business analysts who extracted data from the IW, then cleaned it, integrated additional data and transformed it into their own reports. While this division of labor and IT resources enabled better business decisions because it facilitated better analysis of the available data, it also distributed BI and IS responsibilities and resources across the organization. For example, as many as 100 people were being employed in end-user communities in CTR finance and supply chain in positions that were largely IT responsibilities (technology acquisition and management, application development, database management, technical support, etc.) but who worked outside of governance of the IT function. These shadow IT groups provided an alternative source of IT resources to the user groups but at unknown cost and security risk to the CTC IT infrastructure. By 2003, CTC IT was largely seen as a hardware provider and manager but not as a strategic business partner. CTR marketing maintained its own analysts, developers and end-user support for BI efforts, and CTR FRAG provided most of the retail analytics needed by marketing. Figure 4 provides a depiction of the current architecture of the IW. The major challenges were the multiple independent data sources not included in the IW, lack of standard data definitions and consequent inaccuracies in the data, the strained resources associated with storage and querying the IW, and the increasing delays and denial of access to information required by the end-users. When Wnek assumed the role of CTC CIO, he understood the barriers to BI success. His work in the mid-90s had lead to the initial development of the IW and FRAG. This gave him a good perspective as to what was needed to realize the value of BI. To get the ball rolling, four major activities were undertaken: Four guiding principles were established to support these goals: to be business driven, to support the IT strategy (including making technical changes in line with the technology plan), keep the learning in-house (even if external expertise was used), and make changes sustainable. Effective execution of the BI strategy over the next three years would result in a new BI environment (see Figure 5). In this new world, data would be sourced and consistently managed and integrated from across the company, historical data would be organized according to standard data formats and housed in the central data warehouse, and there would be simple and easy to update access to metadata6 (data about the data). This would result in various data views or data marts.7 Decisions about implementing physical data marts versus special views of the data for different areas had not yet been made. As an example, the financial data mart (or view) would provide consistent access to standard financial data that would be the basis for enterprise performance management. Similarly other areas would have their own data marts/views to assist in their own decisions while masking the complexities associated with access to the full corporate data structure. BI specialists would assist in organizing the data marts/views, retail analytic specialists would have access to BI tools and the data warehouse to perform sophisticated analysis and predictive modeling, and end-users would have instant access to information they needed to make relevant business decisions. Given the current state of BI at Canadian Tire, several steps were planned for the short termnamely dedicating resources to implementing quick win projects and finalizing a detailed BI strategy-and-planning document to serve as a guide for prioritizing actions over the next three years. Quick win opportunity assessments happened in early 2003. These projects consisted of short-term actions that IT could take to improve BI capabilities and to provide users with new information. These included opportunities such as providing access to daily promotional sales data; market basket analysis capabilities; forecasting and model simulation of incremental sales; pricing optimization reports by region; price competitiveness analytics and brand analysis such as comparisons by brand, brand manager, margin, shipments, cannibalization, etc. Quick win projects were selected based on offering the highest potential value at the lowest cost to IT resources. As Eubanks and Wneks meeting progressed, they reflected on the difficulties faced in the next several months. First, they had to determine what to do about new quick win requests while they finalized the BI strategy and implemented the program. On the one hand, what was the point of the BI strategy and program plan if they kept reacting to new quick win requests, rather than using the plan to prioritize them? However, on the other hand, they had to think about the business implications of not delivering new quick win requests that could provide real value to the business today. They wondered whether rejecting new requests would diminish the end-users enthusiasm for the BI initiative and whether the work would be picked up by the shadow IT groups. Second, several elements of the BI strategy still needed to be finalized, and programs, with their ensuing priority and timeline, needed to be developed. Eubanks and Wnek wondered what technological, organizational and people implementation plans would need to be included on the timeline in order to successfully deliver on the BI strategy over the next 2.5 years, given that the organization was expecting the program to be completed by the end of 2005. RBC’s annual investor day will bring together world-leading experts across the data center and connectivity spectrum to discuss emerging infrastructure and technology trends and to explore opportunities for investment and growth throughout the sector. Demand for both data center capacity and connectivity solutions is being driven by a rapid rise in data traffic and ever-increasing reliance on the internet. Data centers provide the foundation for the network and computing solutions that will enable companies to embrace digital transformation and keep pace with rapidly changing technologies. Data center and connectivity providers that are able to stay ahead of IT outsourcing, innovation and technology trends, while positioning themselves for growth, are attracting significant interest from an expanding community of investors. Widescale network infrastructure investment is being channeled to keep pace with the increased adoption of cloud computing – with hyperscale cloud deployments as a particularly notable driver of growth – as well as advancements in 5G, AI, Io T and Edge. Infrastructure requirements to support these advancements, combined with providers looking to gain scale and broaden geographic reach, are fueling M&A opportunities and interest in this dynamic and rapidly growing market. With speakers sharing their market expertise and experiences from around the world, Conference attendees will gain unique insight into the future of this growing sector, providing a deep dive into specific opportunities for industry participants and those looking to invest in them. The Conference will consist of five industry executive panels running over the course of the day. Raging Wire Data Center Stack Infrastructure Stack Path, LLC Stonepeak Infrastructure Partners Superloop Limited Switch, Inc. Investors will have the opportunity to hear from CEOs and leading industry experts about Edge strategies, the latest trends in hyperscale computing, the transformative power of technology and expert analysis of the growing market opportunity, including key market drivers and in-depth conversation on finance and investment in the sector. Tier Point (Cequel 3) Madonna Park has over 20 years of experience as an investment banker and equity research analyst. This venue will offer a unique opportunity to connect with market and financial leaders and discover the global potential that Data Centers and Connectivity present for the investment community. As Global Head of RBC’s Communications Infrastructure coverage group, Madonna is responsible for providing companies in the data center / hosting and fiber sectors with comprehensive financial advisory services, leading a number of marquee M&A transactions across North America, Europe and Asia. 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