Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations


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Let us wish you a happy birthday! Date of Birth. Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Month January February March April May June July August September October November December Year Please fill in a complete birthday Enter a valid birthday. In its seventh edition, the report gives a special focus to the poorest billion. Credit Suisse Research Institute's Global Wealth Report confirmed Switzerland's globally leading position in terms of the nations' wealth.

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In this special report, we take a closer look at the Swiss data and assess the drivers behind Switzerland's impressive performance. In this report, the Credit Suisse Research Institute analyses Switzerland's progress in relation to representation of women on different levels of corporate leadership.


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The assessment covers 78 Swiss corporations and compares their gender diversity levels with European and global peers. A key message from our study "The Credit Suisse Gender Women in Senior Management" was that gender diversity — or the greater representation of women — in senior roles was not just "nice to have" but linked to excess stock market returns and superior corporate profitability.

With investor sentiment now showing signs of improvement after a challenging period in emerging markets, our sixth edition of the CSRI Emerging Consumer Survey provides investors timely insights with which to revisit the theme of a fast developing consumer culture shaped by technological innovation. Against the backdrop of the first interest rate increase by the Federal Reserve in almost a decade, the Credit Suisse Research Institute's Global Investment Returns Yearbook examines similar episodes since and derives potential implications for future economic and financial market developments.

75 Sources of Economic Data, Statistics, Reports, and Commentary

This report by the Credit Suisse Research Institute explores several important aspects of the connection between sound governance and improved business performance. It provides new data to support the growing investor interest in governance-related rules and practices and introduces innovative ways to assess corporate performance.

In its sixth edition, the Credit Suisse Global Wealth Report offers a comprehensive portrait of global wealth, covering all regions and countries, and all parts of the wealth spectrum, from the very base of the wealth pyramid to ultra-high net worth individuals UHNWIs. This report adds to the CS Globalization Index that we introduced in the CSRI 'Success of Small Countries' report by developing a 'Multipolarity Index' and a 'Globalization Clock' and by examining specific trends in financial markets, trade, governance and corporate activity.

This study follows on from our report "Sugar: Consumption at a Crossroads" in examining another key component of nutrition and dietary make-up.

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We scrutinize the ecosystem of "fat", looking at the five types of fats, the main fat-rich foods and who produces them, the medical research on fat and the perception of doctors, consumers and health officials. Entrepreneurship is borne of opportunity and necessity. With increased deregulation and decreased involvement of the State, we have seen that family owned businesses are not just key drivers of economic growth, but are also key employers.

Small countries provide an indication of the future for large coun-tries, and a test bed as to what works and what does not. One innovation in this report is to measure the way in which small countries lead larger ones in terms of economic performance. In the developed world, both equity and bond markets are at record highs. The price of oil has collapsed and the Swiss franc has jettisoned its link with the euro.

Our fifth Emerging Consumer Survey reflects a challenging environment for consumer activity. The prevailing weakness in currencies and commodity prices provides for other sources of concern. However, there are clear winners and losers. You have viewed out of items. Economy in motion. Research publications. Healthcare transformation. Emerging Consumer Survey Assessing Global Debt. Asia in Transition.

Service Industry Databook

Global Wealth Report Global Wealth Databook Accompanying databook to the Global Wealth Report The CS Family in The Future of GDP. Eradicating Extreme Poverty. The Future of Politics. The Swiss Family Business Model. The CS Family Switzerland: A Financial Market History. Getting Over Globalization. The Future of Monetary Policy. Therefore, an implementation of the MapReduce framework was adopted by an Apache open-source project named Hadoop.

A distributed parallel architecture distributes data across multiple servers; these parallel execution environments can dramatically improve data processing speeds.

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This type of framework looks to make the processing power transparent to the end user by using a front-end application server. The data lake allows an organization to shift its focus from centralized control to a shared model to respond to the changing dynamics of information management. This enables quick segregation of data into the data lake, thereby reducing the overhead time.

Big data analytics for manufacturing applications is marketed as a "5C architecture" connection, conversion, cyber, cognition, and configuration. A McKinsey Global Institute report characterizes the main components and ecosystem of big data as follows: [56]. Multidimensional big data can also be represented as data cubes or, mathematically, tensors. Array Database Systems have set out to provide storage and high-level query support on this data type. Additional technologies being applied to big data include efficient tensor-based computation, [57] such as multilinear subspace learning.

Some MPP relational databases have the ability to store and manage petabytes of data. Implicit is the ability to load, monitor, back up, and optimize the use of the large data tables in the RDBMS. DARPA 's Topological Data Analysis program seeks the fundamental structure of massive data sets and in the technology went public with the launch of a company called Ayasdi. The practitioners of big data analytics processes are generally hostile to slower shared storage, [64] preferring direct-attached storage DAS in its various forms from solid state drive SSD to high capacity SATA disk buried inside parallel processing nodes.

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The perception of shared storage architectures— Storage area network SAN and Network-attached storage NAS —is that they are relatively slow, complex, and expensive. These qualities are not consistent with big data analytics systems that thrive on system performance, commodity infrastructure, and low cost. Real or near-real time information delivery is one of the defining characteristics of big data analytics. Latency is therefore avoided whenever and wherever possible. Data in direct-attached memory or disk is good—data on memory or disk at the other end of a FC SAN connection is not.

The cost of a SAN at the scale needed for analytics applications is very much higher than other storage techniques. There are advantages as well as disadvantages to shared storage in big data analytics, but big data analytics practitioners as of [update] did not favour it. Developed economies increasingly use data-intensive technologies. There are 4. The world's effective capacity to exchange information through telecommunication networks was petabytes in , petabytes in , 2. This also shows the potential of yet unused data i. While many vendors offer off-the-shelf solutions for big data, experts recommend the development of in-house solutions custom-tailored to solve the company's problem at hand if the company has sufficient technical capabilities.

The use and adoption of big data within governmental processes allows efficiencies in terms of cost, productivity, and innovation, [68] but does not come without its flaws. Data analysis often requires multiple parts of government central and local to work in collaboration and create new and innovative processes to deliver the desired outcome.

CRVS is a source of big data for governments. Research on the effective usage of information and communication technologies for development also known as ICT4D suggests that big data technology can make important contributions but also present unique challenges to International development. Based on TCS Global Trend Study, improvements in supply planning and product quality provide the greatest benefit of big data for manufacturing.

Big data provides an infrastructure for transparency in manufacturing industry, which is the ability to unravel uncertainties such as inconsistent component performance and availability. Predictive manufacturing as an applicable approach toward near-zero downtime and transparency requires vast amount of data and advanced prediction tools for a systematic process of data into useful information.

Vast amount of sensory data in addition to historical data construct the big data in manufacturing. The generated big data acts as the input into predictive tools and preventive strategies such as Prognostics and Health Management PHM. Big data analytics has helped healthcare improve by providing personalized medicine and prescriptive analytics, clinical risk intervention and predictive analytics, waste and care variability reduction, automated external and internal reporting of patient data, standardized medical terms and patient registries and fragmented point solutions.

The level of data generated within healthcare systems is not trivial. With the added adoption of mHealth, eHealth and wearable technologies the volume of data will continue to increase. This includes electronic health record data, imaging data, patient generated data, sensor data, and other forms of difficult to process data. There is now an even greater need for such environments to pay greater attention to data and information quality.

A related application sub-area, that heavily relies on big data, within the healthcare field is that of computer-aided diagnosis in medicine.

Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations
Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations
Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations
Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations
Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations
Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations Service Industry Databook: Understanding and Analyzing Sector Specific Data Across 15 Nations

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