With the advent of big data, organizations worldwide are
attempting to use data and analytics to solve problems previously
out of their reach. Many are applying big data and analytics
to create competitive advantage within their markets, often
focusing on building a thorough understanding of their
High-priority big data and analytics projects often target
customer-centric outcomes such as improving customer loyalty
or improving up-selling. In fact, an IBM Institute for Business
Value study found that nearly half of all organizations with active
big data pilots or implementations identified customer-centric
outcomes as a top objective (see Figure 1).1 However, big data
and analytics can also help companies understand how changes
to products or services will impact customers, as well as address
aspects of security and intelligence, risk and financial management,
and operational optimization.
An IBM white paper describing the infrastructure implications of today’s converging technology forces and the software defined, next-generation data center transformation vital to capitalizing on them.
Learn from this TDWI paper how right-sized information governance can improve the success of data warehousing or big data analytics initiatives, and how a chief data officer can help organizations to appreciate the value of data and its importance to their decisions and operations.
Businesses that exploit Big Data to improve strategy and execution are distancing themselves from competitors. The Big Data solution from EMC provides market-leading, scale-outing storage, a unified analytics platform, and business process and application development tools. Together, these allow organizations to draw deeper insights and become a more predictive organization.
Forward-looking enterprises know there's more to big data than strong and managing large volumes of information. Big data presents an opportunity to leverage analytics and experiment with all available data to derive value never before possible with traditional business intelligence and data warehouse platforms. Through a modern, big data platform that facilitates self-service and collaborative analytics across all data, organizations become more agile and are able to innovate in new ways.
While the concept of big data is nothing new, the tools and technology and now in place for companies of all types and sizes to take full advantage. Enterprises in industries such as media, entertainment, and research and development have long been dealing with data in large volumes and unstructured formats - data that changes in near real time. However, extracting meaning from this data has been prohibitive, often requiring custom-built, expensive technology. Now, thanks to advancements in storage and analytics, all organizations can leverage big data to gain the insight needed to make their businesses more agile, innovative, and competitive.
Competitive enterprises that embark on big data strategies do so with the expectation that their businesses will transform. They don't just want answers from the data they collect and analyze, they want results. Be it with small, fledgling trials or large, cross-functional efforts, these enterprises want to see clearly how big data can make a difference - with their customers, their processes, their bottom lines and, most important, with growing the business.
Published By: Workday
Published Date: Aug 07, 2018
Today, big data is everywhere. But only companies that know how to realize its true potential are gaining the competitive edge. Join HBR and Eric Siegel, author of Predictive Analytics: Who Will Click, Buy, Lie, or Die, to learn how you can transform data into insight, predict the future, and win.
"Today, enormous amounts of data are being created from a variety of sources, such as applications, new mobile devices, big data analytics, and the cloud. This is changing the speed with which business gets conducted and the scale in which it occurs. Moreover, the digital explosion shows no sign of slowing and IDC expects the amount of data being stored to grow in excess of 50% per year over the next few years.
Discover how flash technology is being deployed to improve performance and efficiency for these demanding environments. Access this IDC whitepaper to learn more about the role of flash technology and the importance of flash solutions that are designed specifically for the enterprise."
Download this eBook to learn the steps you can take now to prepare for the all flash data center.
flash storage, SSD, all flash data centers, nimble storage, predictive flash platform, application perfomance, data velocity
The very best CFOs are becoming “technology evangelists”, investing in the latest mobile, social, analytical and cloud technologies to modernize their finance organizations and become more strategic partners to the business. Find out more – download the report, “Empowering Modern Finance: The CFO as Technology Evangelist.”
Published By: ClearStory
Published Date: Oct 07, 2014
When it comes to “big data,” Gartner boils it all down to “value.” In their 2014 Cool Vendors for Big Data report, ClearStory Data was among 4 companies profiled. According to Gartner, ClearStory is “for companies looking at big data business intelligence and analytics from a data variety perspective.”
As any line of business (LOB) leader knows, making customer level decisions that balance risk and profit just keeps getting harder. And even when you think you have the right decisions, turning them into actions can be even trickier. You also need to consider the factors that make smart decisions difficult. Big data. Regulations. Customers who want an offer, fast, or else you’re going to lose them.
With the increasing mainstream adoption of big data infrastructure — highly distributed file storage and query tools — more businesses are taking a new look at what business intelligence and analytics can do to grow revenue, increase profits and ultimately develop strategic relationships with customers.
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences.
Download the e-book to learn how:
Micron Technology reduced number of IT incidents by more than 50%
Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events
TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences.
Download this executive brief from CIO to learn:
5 steps to an effective predictive IT strategy
Where AI can help, and where it can’t
How to drive revenue and exceptional customer experiences with predictive analytics
As easy as it is to get swept up by the hype surrounding big data, its just as easy for organisations to become discouraged by the challenges they encounter while implementing a big data initiative. Concerns regarding big data skill sets (and the lack thereof), security, the unpredictability of data, unsustainable costs, and the need to make a business case can bring a big data initiative to a screeching halt.
However, given big data's power to transform business, it's critical that organisations overcome these challenges and realise the value of big data. The cloud can help organisations to do so. Drawing from IDG's 2015 Big Data and Analytics Survey, this white paper analyses the top five challenges companies face when undergoing a big data initiative and explains how they can effectively overcome them.
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization.
This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions.
Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
Apache® Spark™ has become a vital technology for
development teams looking to leverage an ultrafast
in-memory data engine for big data analytics. Spark
is a flexible open-source platform, letting developers
write applications in Java, Scala, Python or R. With
Spark, development teams can accelerate analytics
applications by orders of magnitude
This white paper describes how IBM’s Pure Data System for Analytics delivers speed and simplicity to help organizations become more responsive and agile in today’s increasingly mobile and data-driven market.
Big Data has generated much interest and attention in the media of late. Indeed, several authors have recently raised the question of whether Big Data approaches, such as Hadoop, will pronounce the death sentence on the conventional data warehouse.
In this survey we investigate the current state of the data warehouse and examine its recent challenger in the form of Big Data solutions as an alternative. Is the new technology really complementary or is the reign of the data warehouse nearing an end?
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