Tips and best practices for data analytics executives
Organizations today understand the value to be derived from arguably their greatest asset—data. When successfully aggregated and analyzed, data can unlock valuable insights, solve problems, improve products and services, and help companies gain a competitive edge. However, analytics executives face significant challenges in collecting, validating and analyzing data to deliver the right analytic insight to the right person at the right time.
This e-book is designed to help. First, we'll explore the growing expectations for data analytics and the rise of the analytics executive. Then we'll explore a range of specific challenges those executives face, including those around data blending, analytics, and the organization itself, and offer best practices and strategies for meeting them.
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Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
Although data and analytics are highlighted throughout the popular press as well as in trade publications, too many managers think the value of this data processing is limited to a few numerically intensive fields such as science and finance. In fact, big data and the insights that emerge from analyzing it will transform every industry, from “precision farming” to manufacturing and construction. Governments must also be alert to the value of data and analytics as the enabler for smart cities. Institutions that master available data will leap ahead of their less statistically adept competitors through many advantages: finding hidden opportunities for efficiency, using data to become more responsive to clients, and developing entirely new and unanticipated product lines. The average time spent by most companies on the S&P 500 Index has decreased from an average of 60 to 70 years to only 22 years. There are winners and losers in the changes that come with the evolution of both technology
Published By: Cisco EMEA
Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
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Do you know your people as well as you know your customers? Your people’s expectations and the way they work are changing. Employees are more diverse, mobile and technologically savvy than ever before. HR processes are changing from focusing on transactions to knowing and engaging people. Just as sales and marketing teams use data to develop actionable and informed insights about their customers, you need to do the same in HR to know your people. Everything from attracting and keeping the best talent to creating better workplace experiences and increasing employee engagement and productivity, depends on smarter decisions. These in turn rely on more actionable insights. These are only possible through accurate HR data and analytics. They are vital to address the people challenges you face, so you can make smarter decisions. Discover in this guide how to improve visibility of your workforce with data-driven and actionable insights. Ultimately, it will help you know your people better and
In the age of the customer, businesses realize the need to take their big data insights further than they have before, in order to win, serve, and retain their customers. Today’s modern company has more data than ever before and is now looking to derive insights from the data that will help propel it forward. As firms move data analytics to the cloud, there is a new set of challenges and barriers to overcome, but with the help of insights-platforms-as-a-service, companies will be able to innovate with data and drive business forward.
The Industrial Internet of Things (IIoT) is flooding today’s industrial sector with data. Information is streaming in from many sources — equipment on production lines, sensors at customer facilities, sales data, and much more. Harvesting insights means filtering out the noise to arrive at actionable intelligence.
This report shows how to craft a strategy to gain a competitive edge. It explains how to evaluate IIoT solutions, including what to look for in end-to-end analytics solutions. Finally, it shows how SAS has combined its analytics expertise with Intel’s leadership in IIoT information architecture to create solutions that turn raw data into valuable insights.
It’s a social world and the majority of organizations today use Microsoft Office as their chosen office productivity suite. So it’s important to deliver insights where people are working most. This paper shows how you can use results produced by SAS Visual Analytics with Microsoft Office applications – Outlook, Excel, Word, PowerPoint and SharePoint. With plenty of how-to specifics, you’ll see how easy it is to combine analytic visualizations and reports with Microsoft products to share insights, improve collaboration and drive further adoption of analytics across your organization.
What do these market-defining trends have in common?
· Analytics for all
· Analytics as competitive differentiator
· Internet of Things
· Artificial intelligence/Machine learning/Cognitive computing
· Real-time analytics/event management
They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise?
It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i