Using data to reinvent one’s business has reached the mainstream. Data and analytics allow us to change the world around us: it gives us insights into what is happening, allowing us to optimize our strategy, create new business opportunities, and make more accurate predictions.
Today’s digital businesses are managed using critical business analyses that provide far greater insight into the business and how to maximize results. However, these high-value applications that use the latest software tools demand far more from IT infrastructure, as they utilize an order of magnitude more data and demand more compute resources than legacy applications. Legacy systems are no longer capable of meeting the present and future needs of the organization.
Today’s digital businesses are managed using critical
business analyses that provide far greater insight into
the business and how to maximize results. However,
these high-value applications that use the latest
software tools demand far more from IT infrastructure,
as they utilize an order of magnitude more data and demand
more compute resources than legacy applications.
Legacy systems are no longer capable of meeting the
present and future needs of the organization.
Data professionals now have the freedom to create, experiment, test and deploy different methods easily – using whatever skill set they have – all within one cohesive analytics platform. IT leaders gain the ability to centrally manage the entire analytics life cycle for both SAS and other assets with one environment. Organizations get faster results and better ROI from analytics efforts.
This collection is part of the ANA Magazine Thought Leadership Series sponsored by SAS. The articles explore the variety of ways to use analytics to create marketing functions that are more accountable and profitable.
Recent Gartner research indicates that the confluence of information generated by new technologies and sources such as cloud computing will create a nexus of forces that could be even more disruptive than the dot-com and e-business booms of the 1990s
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.
The headlines and major company announcements share a common theme:
Competitive disruption is reshaping business models and organizations’ very futures.
Around the global automotive industry, component and original equipment
manufacturers (OEMs) are taking a hard look at where their future growth will come
from ? and it’s not all based on their core businesses. New technology has opened the
door for new services and revenue streams.
Agencies have long provided telecommunications companies with scalability for collections in a high-growth industry. Today, with markets and business models changing, your collections agencies have a growing impact — for good or ill — on your success.
With so much emphasis in the business world being placed on big data and analytics, it can be easy for midsize businesses to feel like they’re being left behind. These organizations often recognize the benefits offered by big data and analytics, but have a hard time pursuing those benefits with the limited resources available to them.
When was the last time you had an outstanding customer experience? Perhaps you hesitated before answering. Now, think for a minute about your customers – would they hesitate before answering the same question about your business? If you think the answer might be yes, it’s time to consider the customer journey.
Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally.
Learn more about key findings, including:
Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics.
Return on investment for analytics stems from the governing and sharing of data throughout the organization.
Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.
There is a movement towards advanced and
predictive analytics in the Learning and Talent
Management space. But what does that really mean?
Bluewater’s team of consultants and developers can
help you define what analytics means for your
This report explores how cloud-based solution providers, such as managed service providers (MSPs) and independent software vendors (ISVs) are using an embedded approach to analytics in an effort to empower their customers and build a competitive advantage.
5 to 10 minute Video of Glenn O' Donnell from Forrester talking to IBM General Manager Deepak Advani about the new era of Analytics emerging in the IT space to help IT Predict outages before they occur, find resolution to problems faster and optimize for performance.
The volume of customer data that marketing departments possess continues to grow at explosive rates. But new research from the Aberdeen Group finds that less than 40% of marketers use this information to optimize and target their campaigns. This "data rich, insight poor" phenomenon is examined in their new white paper, which identifies common analytics challenges-and shows how you can rise above them.
To determine the status of Analytics and Business Intelligence in the Cloud, Enterprise Management Associates (EMA) embarked on an end-user research study to look at the current state of cloud-based analytics. Read the white paper to discover panelists’ insights on cloud-based analytics, business intelligence strategies, and implementation practices.
What is your Analytics Maturity?
An 'Army of Analysts' can be very powerful.
The problem, of course, is that as your organisation scales, and more data requests come in, you’ll constantly be hiring more analysts (and that gets expensive!).
Download this infographic to discover what your analytics maturity is, and how to move from an 'Army of Analysts' to a more efficient, scalable model.