Published By: Sage EMEA
Published Date: Jan 29, 2019
Transform your finance operations into a strategic, data-driven engine
Data inundation and information overload have burdened practically every largescale enterprise today, providing great amounts of detail but often very little context on which executives can act. According to the Harvard Business Review,1 less than half of an organisation’s structured data is actively used in making decisions.
The burden is felt profoundly among finance executives, who increasingly require fast and easy access to real-time data in order to make smart, timely, strategic decisions. In fact, 80% of analysts’ time is spent simply discovering and preparing data, and the average CFO receives information too late to make decisions 24% of the time.2
Web applications are valuable tools for businesses of all sizes. These applications enable businesses to communicate with customers, prospects, employees, partners, and other information technology (IT) systems. By definition, web applications must be open, interactive, and accessible at all times.. This report, authored by Frost & Sullivan analysts, takes a comprehensive look at the current Web Application Firewall (WAF) vendor landscape and analyzes the current web application threat landscape and how vendors will scale to face it.
There are four IT megatrends that will transform IT and the business in the next few years. These four trends are all connected, all overlapping, all a part of an overall enterprise transformation. Success with these trends will be the primary driver for success in a world that is becoming much more digital and real-time. But many companies are still failing to connect the dots. Listen as Gartner VP Distinguished Analyst Tom Bittman discusses how to effectively navigate the four megatrends as a part of a holistic enterprise transformation the drives results.
Published By: Dell EMC
Published Date: Aug 06, 2018
Download this whitepaper for 4 reasons shorter server resfresh cycles are better for business.
Analyst firm IDC reports that organizations can increase agility, improve efficiency and reduce operational costs by refreshing their servers every three years.
If you are working with massive amounts of data, one challenge
is how to display results of data exploration and analysis in a
way that is not overwhelming. You may need a new way to look
at the data – one that collapses and condenses the results in an
intuitive fashion but still displays graphs and charts that decision
makers are accustomed to seeing. And, in today’s on-the-go
society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time.
SAS® Visual Analytics is a data visualization and business
intelligence solution that uses intelligent autocharting to help
business analysts and nontechnical users visualize data. It
creates the best possible visual based on the data that is
selected. The visualizations make it easy to see patterns and
trends and identify opportunities for further analysis.
How are organizations balancing self-service analytics and data governance today? What are the trends for tomorrow?
Many organizations are on their way to achieving self-service analytics maturity through the use of intuitive data visualization technologies aimed at non-technical users; as well as various tactics that reduce reliance on IT. But handing the analytics reins entirely to business users can make governance nearly impossible. As a result, organizations are increasing investments in modern analytics platforms that enable a balance between IT governing and curating data, empowering business users to derive insights from data mostly on their own and without delay.
Join guest speaker, Forrester Research VP and Principal Analyst, Boris Evelson and Oracle Analytics Senior Group Director, Jose Villacis as they discuss insights from an Oracle-commissioned study of North American enterprise analytics leaders.
When asked how important technology is to driving innovation in their organizations, 100 percent of CEOs indicated it was important, with 80 percent pointing out that it’s very important, according to HP sponsored research. Even CIOs agree with their CEOs.
According to the same research, when asked whether or not technology will be the innovation engine or administrative engine for a business or government, approximately two out of three CEOs said it would be the “innovation engine.” This represents a significant shift in the role that technology is playing in enterprises.
Today, organizations demand new applications and more functionality delivered more quickly, and at a lower cost than ever before. Many organizations either want a mobile application or are already using one. In fact, according to analysts, by 2016 350 million employees will use smartphones at work and businesses will increase spending on mobile projects over 100 percent in the same time.
In this whitepaper, we describe how executive and IT management can get and maintain control of their company's data architecture to help meet business objectives. We describe the relationship between data integration projects and data architecture concepts and practices. We describe how the business planning and IT development processes that direct and leverage data integration projects depend on tooling. We describe breakthrough ways in which data architects, business analysts, programmers, and business users can collaborate to address their organization's pressing business challenges.
Mainframes continue to provide high business value by combining efficient transaction processing with high-volume access to critical enterprise data. Business organizations are linking mobile devices to mainframe processing and data to support digital applications and drive business transformation. In this rapidly growing scenario, the importance of providing excellent end-user experience becomes critical for business success.This analyst announcement note covers how CA Technologies is addressing the need for providing high availability and a fast response time by optimizing mainframe performance with new machine learning and analytics capabilities.
Whilst businesses of all kinds are utilizing data analytics, many are still only using it to make simple changes that lead to a set of rigid processes. Whereas the more customer-focused organizations are realizing that to deliver exceptional experiences, they need to be able to react to customer data in real-time and predict what might happen next. And that means going beyond simple analytics.
Read our whitepaper to discover what analyst firm Forrester has identified as the Enterprise Insight Platform, technology designed to enable companies to transform into truly data-driven businesses.
Published By: Trifacta
Published Date: Feb 12, 2019
Over the past few years, the evolution of technology for storing, processing and analyzing data has been absolutely staggering. Businesses now have the ability to work with data at a scale and speed that many of us would have never thought was possible. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with people. In this latest Data Science Central webinar, guest speakers Forrester Principal Analyst Michele Goetz and Trifacta Director of Product Marketing Will Davis focus on the roles and responsibilities required for today’s modern dataops teams to be successful. They touch on how new data platforms and applications have fundamentally changed the traditional makeup of data/analytics organizations and how companies need to update the structure of their teams to keep up with the accelerate pace of modern business. Watch this recorded webcast to learn: What are the foundational roles within a modern dataops team a
Published By: Trifacta
Published Date: Feb 12, 2019
In recent years, a new term in data has cropped up more frequently: DataOps. As an adaptation of the software development methodology DevOps, DataOps refers to the tools, methodology and organizational structures that businesses must adopt to improve the velocity, quality and reliability of analytics. Widely recognized as the biggest bottleneck in the analytics process, data preparation is a critical element of building a successful DataOps practice by providing speed, agility and trust in data.
Join guest speaker, Forrester Senior Analyst Cinny Little, for this latest webinar focusing on how to successfully select and deploy a data preparation solution for DataOps. The presentation will include insights on data preparation found in the Forrester Wave™: Data Preparation Solutions, Q4 2018.
In this recorded webinar you will learn:
• Where does data preparation fit within DataOps
• What are the key technical & business differentiators of data preparation solutions
• How to align the righ
Published By: Trifacta
Published Date: Feb 12, 2019
Over the past few years, the evolution of technology for storing, processing and analyzing data has been absolutely staggering. Businesses now have the ability to work with data at a scale and speed that many of us would have never thought was possible. Yet, why are so many organizations still struggling to drive meaningful ROI from their data investments? The answer starts with people.
In this webinar, guest speakers Forrester Principal Analyst Michele Goetz and Trifacta Director of Product Marketing Will Davis focus on the roles and responsibilities required for today’s modern dataops teams to be successful. They touch on how new data platforms and applications have fundamentally changed the traditional makeup of data/analytics organizations and how companies need to update the structure of their teams to keep up with the accelerate pace of modern business.
Watch this recorded webcast to learn:
What are the foundational roles within a modern dataops team and how to align skill set
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before.
These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
Published By: Equinix
Published Date: Oct 27, 2014
The businesses that thrive amid fluctuating technology demands are not only keeping a finger on the pulse of current trends, they have the infrastructure in place to handle whatever changes might come. And they’re doing so by treating their data centers as a strategic asset—a hub from which providers and performance can all stem.
Are you ready for what’s next? According to analyst forecasts and
IT executives, the five key trends affecting our state of technology are mobility, consumer technology, cloud services, hyperdigitization and globalization. In the following pages, you’ll learn how these bgtrends are affecting current networks, and why a strategic data center is key to not only surviving, but thriving, today and in the future.
Published By: Datawatch
Published Date: Feb 03, 2016
Some companies estimate that up to 80 percent of their analysts’ time is spent on data preparation. Thorough, automated data preparation, however, can quickly transform raw information into reliable, consistent data sets ready for analysis. This report from Gartner details why information management and business analytics leaders must introduce data preparation into their big data initiatives in order to improve both the understanding of the data, and the productivity of analysts. Read the report now to learn more.
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them?
Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency
Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making.
Download this new paper to get the details behind self-service data analytics, and how it lets business analysts:
Take charge of the entire analytical process, instead of relying on other departments
Overcome limitations of legacy tools to save time and prevent errors
Make more comprehensive and insightful business decisions at speed
Data inundation and information overload have burdened practically every largescale enterprise today, providing great amounts of detail but often very little context on which executives can act. According to the Harvard Business Review, less than half of an organization’s structured data is actively used in making decisions.
The burden is felt profoundly among finance executives, who increasingly require fast and easy access to real-time data in order to make smart, timely, strategic decisions. In fact, 80% of analysts’ time is spent simply discovering and preparing data, and the average CFO receives information too late to make decisions 24% of the time.
Published By: Datarobot
Published Date: May 14, 2018
The DataRobot automated machine learning platform captures the knowledge, experience, and best practices of the world’s leading data scientists to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods
Constant market shifts and changing customer preferences add to the challenge of
outperforming your competitors and surpassing stakeholder expectations. But what
can be done to steer your organization down the path to greater success?
By now, we all know it’s not just historical reporting about the past that will provide the
answers needed to drive a business forward. Everyone – from executives and analysts
to frontline staff – must have access to insights about the future that will enable them to
make the best decisions and take the actions needed to keep their organizations agile.
This means the ability to peer into data, explore it, understand it, analyze it and produce
insights that provide those aha moments and take actions on it. Such things cannot be
done with multiple tools that are rigid, limiting and difficult to use. A new breed of
business intelligence is required.
Gone are the days when reports looked at singular issues, took possibly days or weeks
to create, and required
Many organizations consider optimization only for their largest or most challenging business problems, often utilizing a small number of Operations Research professionals. But in our age of Big Data, market globalization and increased competition, many organizations are successfully making the case that optimization can be applied to a wider variety of business and operational decisions, and be developed by a new group of users — the organization’s business analysts.
With a proven track record of results demonstrating that organizations can increase profitability with business analysts applying optimization to many types of business problems, FICO’s proven development methodology is giving organizations the confidence to extend optimization practices across their enterprises.
Published By: Genesys
Published Date: Jun 13, 2018
When building artificial intelligence (AI) into your business strategy, it’s easy to become distracted by all the new technologies on the market—each one promising a better customer experience. Make decisions based on facts, not misconceptions.
When you evaluate AI technologies, consider these facts:
• Bots working with human agents enables a seamless customer journey
• Automated self-service costs as little as 20 cents per interaction
• A single platform makes it easier to deliver personalized, proactive and predictive experiences
See how AI connects customer conversations in this new analyst guide, 2017 ContactBabel Inner Circle Guide to Self-Services.