Published By: Oracle OMC
Published Date: Nov 30, 2017
The face of retail – both online and instore – is rapidly evolving. In addition to margin pressures, resource constraints, and competitive challenges retailers face on an ongoing basis, many are struggling to keep up with the evolving demands of vocal consumers. As new channels and buying habits emerge and evolve, many retail marketers have struggled to keep up. Although many have adopted new technologies to address new channels and challenges, the rapid pace of technological change has created new challenges including:
E-mail marketing overload
Channel coordination and conflict
These challenges, coupled with the rising cost of acquiring and managing customer data, are compounded by increasing scrutiny on marketing budgets and an expectation of being able to prove the value of every campaign in terms of increased revenues.
There can be no doubt that the architecture for analytics has evolved over its 25-30 year history. Many recent innovations have had significant impacts on this architecture since the simple concept of a single repository of data called a data warehouse.
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
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.
For increasing numbers of organizations, the new reality for development, deployment and delivery of applications and services is hybrid cloud. Few, if any, organizations are going to move all their strategic workloads to the cloud, but virtually every enterprise is embracing cloud for a wide variety of requirements.
To accelerate innovation, improve the IT delivery economic model and reduce risk, organizations need to combine data and experience in a cognitive model that yields deeper and more meaningful insights for smarter decisionmaking. Whether the user needs a data set maintained in house for customer analytics or access to a cloud-based data store for assessing marketing program results — or any other business need — a high-performance, highly available, mixed-load database platform is required.
As organizations develop next-generation applications for the digital era, many are using cognitive computing ushered in by IBM Watson® technology. Cognitive applications can learn and react to customer preferences, and then use that information to support capabilities such as confidence-weighted outcomes with data transparency, systematic learning and natural language processing.
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization.
Rapid data growth and inefficient data protection systems cause many organizations to spend money in ways they'd rather not. Learn 10 ways that IBM data protection solutions can help organizations modernize infrastructure and save money - freeing up funds to invest in new ideas.
IBM® Information Governance Catalog helps you understand your
information and foster collaboration between business and IT by establishing
a common business vocabulary on the front end, and managing
data lineage on the back end. By leveraging the comprehensive capabilities
in Information Governance Catalog, you are better able to align IT
with your business goals.
Information Governance Catalog helps organizations build and maintain
a strong data governance and stewardship program that can turn data into
trusted information. This trusted information can be leveraged in various
information integration and governance projects, including big data integration,
master data management (MDM), lifecycle management, and
security and privacy initiatives.
In addition, Information Governance Catalog allows business users to
play an active role in information-centric projects and to collaborate with
their IT teams without the need for technical training. This level of governance
and collaboration c
Scalable data platforms such as Apache Hadoop offer unparalleled cost
benefits and analytical opportunities. IBM helps fully leverage the scale
and promise of Hadoop, enabling better results for critical projects and
key analytics initiatives. The end-to- end information capabilities of
IBM® Information Server let you better understand data and cleanse,
monitor, transform and deliver it. IBM also helps bridge the gap between
business and IT with improved collaboration. By using Information
Server “flexible integration” capabilities, the information that drives business
and strategic initiatives—from big data and point-of- impact analytics
to master data management and data warehousing—is trusted, consistent
and governed in real time.
Since its inception, Information Server has been a massively parallel
processing (MPP) platform able to support everything from small to very
large data volumes to meet your requirements, regardless of complexity.
Information Server can uniquely support th
Data is the lifeblood of business. And in the era of digital business,
the organizations that utilize data most effectively are also the most
successful. Whether structured, unstructured or semi-structured,
rapidly increasing data quantities must be brought into organizations,
stored and put to work to enable business strategies. Data integration
tools play a critical role in extracting data from a variety of sources and
making it available for enterprise applications, business intelligence
(BI), machine learning (ML) and other purposes. Many organization
seek to enhance the value of data for line-of-business managers by
enabling self-service access. This is increasingly important as large
volumes of unstructured data from Internet-of-Things (IOT) devices
are presenting organizations with opportunities for game-changing
insights from big data analytics. A new survey of 369 IT professionals,
from managers to directors and VPs of IT, by BizTechInsights on
behalf of IBM reveals the challe
Published By: QASymphony
Published Date: Jan 08, 2018
Data. It seems to be everywhere today and yet we can never get
enough of it. But as it turns out, a lack of data isn’t our problem
-- our problem is the difficulty piecing together, understanding and
finding the story in all the data that’s in front of us.
In software testing in particular, the need for consolidated,
meaningful test metrics has never been higher. As both the pace of
development and the cost of delivering poor quality software
increase, we need these metrics to help us test smarter, better and
Fortunately, business intelligence now exists to make this goal a
reality. The analytics these tools provide can help drive efficient
and effective testing by providing teams with insight on everything
from testing quality and coverage to velocity and more. And this
knowledge can position the QA team as trusted experts to advise
the entire software development team on steps that can ensure a
better quality end result.
Like many brands with a large footprint of physical store locations, this automotive retailer was having trouble connecting its online ad spend to actual in-store revenue.
In order to reach online consumers, their digital marketing strategy had been buying clicks (CPC) and impressions (CPM). They realized these methods were lacking because:
- They had no true gauge of what ads were working - Their ROI was often inflated by making assumptions instead of using data - It required a heavy upfront investment
Published By: Tenable
Published Date: Feb 07, 2018
"This IDC Technology Spotlight examines the evolution of vulnerability management. By leveraging the cloud and new technologies that deliver greater visibility, organizations can gain an accurate picture of their assets and overall risk posture. This is a critical step toward addressing the current landscape where attackers are using a wide variety of vectors such as mobile, social, and cloud-based attacks to infiltrate organizations and steal data.
By reading this report you will get an overview of:
- Benefits of cloud-based security and vulnerability management
- Challenges of adopting cloud-based vulnerability management
- IDC assessment of Tenable.io cloud vulnerability management"
The Dell EMC All-Flash storage solution is versatile like a swiss army knife. They have a full suite of best-of-breed products that provide organizations the flexibility to meet their data storage requirements. They allow organizations to customize and choose across best-of breed solutions to meet their needs.
Am Ende steht fest, dass das All-Flash-Speicherarray Dell EMC VMAX 250F seine Versprechen besser erfüllt als das Speicherarray HPE 3PAR 8450.
Das Speicherarray VMAX 250F verarbeitete Transaktions- und Data-Mart-Ladevorgänge zeitgleich mit einer minimalen Auswirkung auf Datenbankperformance. Das ist von Vorteil, wenn Sie umfassende Backups erstellen oder große Datenmengen aus verschiedenen Quellen sammeln.