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Published By: Group M_IBM Q3'19     Published Date: Jun 24, 2019
Delivering personalized customer experience remains the top business challenge for communications service providers (CSPs). Ovum's recently published 2018 ICT Enterprise survey saw almost all CSP IT executives interviewed identify delivering personalized customer experience as one of their three most important business challenges for the next 18 months. This trend emphasizes the high priority CSPs place on how customer relationships are managed. However, several factors have an impact on CSPs' ability to identify and then deliver customers' core needs. These include understanding the data sets they should focus on; collecting, cleansing, and consolidating these data sets; and having the right expertise to mine the data sets.
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Group M_IBM Q3'19
Published By: Google - SAP     Published Date: Jun 20, 2019
According to SiriusDecisions, 79% of companies miss their forecast by 10% or more. Pipeline management is often mismanaged and sales forecasting often off-base. Getting accurate and reliable information about the state of the deals in your pipeline is the key to a happy sales force. Accurate pipeline information also is the foundation of predictable and reliable sales forecasts. Wouldn’t a sales forecast that’s right all of the time be a boon to your organization? Download our new eBook “Pipeline Management and Forecasting are Key to Improving the Sales Experience” to find out how automated tools, AI, and clean data sets can help you as a sales manager to: ? Eliminate the mid-pipeline “black hole” and find out what’s really going on ? Use signals outside of your CRM to get scarily accurate deal opportunity scores and quarterly forecasts. ? Help align the customer journey with your sales process and get happy customers and happy sales reps
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Google - SAP
Published By: Motorola Solutions     Published Date: May 21, 2019
When it comes to worker safety, efficiency and production, nothing is faster than right now. Organizations across various energy segments — oil, gas, petrochemical, electric utilities, water utilities and mining — are currently juggling a mix of communications solution devices and are hindered by gaps in coverage, poor battery life and fragile equipment that cannot withstand harsh environmental conditions. The power of now puts instant communications at your workers’ fingertips — because when communication slows, operation slows. Citizens rely on their homes being heated in the winter, clean running water and lights that turn on when they flip the switch. Meeting these expectations requires reliable, clear voice and data communications for energy workers day-in and day-out. So workers can communicate safely in hazardous environments. So precious resources are not wasted and efficient operations are maintained. So energy companies can continue to exceed expectations. Unified communicati
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Motorola Solutions
Published By: Intapp     Published Date: May 10, 2019
The Cornerstone of Financial Control Time equals money. Time plus data equals control. All professionals, whether in management, consulting, engineering, or accounting, must be confident that their value is reflected in their bottom line. One of the primary factors driving that compensation is the amount of time spent on a particular subject or client. But too often front line earners at those firms don’t provide the clean, data-rich timesheets needed to accurately gauge the effort required by each project.
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business, business intelligence, time, tax, time for tax, intapp, applications, time data, automation, reporting, timekeeping, audit, accounting, consulting, professional services, active time capture, passive time capture, time tracking
    
Intapp
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Delivering personalized customer experience remains the top business challenge for communications service providers (CSPs). Ovum's recently published 2018 ICT Enterprise survey saw almost all CSP IT executives interviewed identify delivering personalized customer experience as one of their three most important business challenges for the next 18 months. This trend emphasizes the high priority CSPs place on how customer relationships are managed. However, several factors have an impact on CSPs' ability to identify and then deliver customers' core needs. These include understanding the data sets they should focus on; collecting, cleansing, and consolidating these data sets; and having the right expertise to mine the data sets.
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Group M_IBM Q2'19
Published By: Claravine     Published Date: Jan 03, 2019
Marketers have long struggled with the simple task of knowing which marketing spend is truly effective, and how to optimize that spend. At the heart of the issue lies the challenge of ensuring the data quality and consistency exists to make decisions based on real intelligence. Why is this a problem? First, effective tracking is reliant on the consistent, complete application of campaign tracking codes and associated metadata, which has traditionally been a manual, ungoverned process. Adding to this complexity has been the dramatic expansion of digital marketing point solutions, and the disparate teams expected to execute across each of these channels and geographies. The result is what you would expect—highly inaccurate, incomplete, and inconsistent data that must be manually cleaned before reporting is possible. Fortunately a solution exists. Progressive marketing leaders are implementing Digital Experience Data Management (DXDM), ensuring the rich, consistent insights critical to ma
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Claravine
Published By: Motorola Solutions     Published Date: Nov 29, 2018
In today’s increasingly mobile world, Energy workers require instant communication and access to data intelligence wherever the job may take them. From the oil rig to the electric grid and everywhere in between, having the right data, in the right hands, at the right time, no matter the environment or device of choice — is simply non-negotiable. Organizations across various Energy segments — oil & gas, electric utilities, water utilities, and mining — are currently juggling a mix of communication devices and are hindered by gaps in coverage, poor battery life and fragile equipment that cannot withstand harsh environmental conditions. Yet, citizens rely on their homes being heated in the winter, on clean running water, and on lights that turn on when they flip the switch. Meeting these expectations requires reliable, clear voice and data communications for Energy workers day-in and day-out. So oil & gas workers can communicate safely in hazardous environments. So precious resources are
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Motorola Solutions
Published By: Dell EMC Storage     Published Date: Nov 28, 2018
Powerful data protection in a converged appliance that is easy to deploy and manage — at the lowest cost-to-protect. The integrated appliance brings together protection storage and software, search, and analytics — plus simplified system management and cloud readiness. And, the IDPA System Manager, with its clean, intuitive interface, provides a comprehensive view of data protection infrastructure from a single dashboard.
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Dell EMC Storage
Published By: Talend     Published Date: Nov 02, 2018
Siloed data sources, duplicate entries, data breach risk—how can you scale data quality for ingestion and transformation at big data volumes? Data and analytics capabilities are firmly at the top of CEOs’ investment priorities. Whether you need to make the case for data quality to your c-level or you are responsible for implementing it, the Definitive Guide to Data Quality can help. Download the Definitive Guide to learn how to: Stop bad data before it enters your system Create systems and workflow to manage clean data ingestion and transformation at scale Make the case for the right data quality tools for business insight
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Talend
Published By: Group M_IBM Q418     Published Date: Oct 15, 2018
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data. Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
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Group M_IBM Q418
Published By: SAS     Published Date: Aug 28, 2018
“Unpolluted” data is core to a successful business – particularly one that relies on analytics to survive. But preparing data for analytics is full of challenges. By some reports, most data scientists spend 50 to 80 percent of their model development time on data preparation tasks. SAS adheres to five data management best practices that help you access, cleanse, transform and shape your raw data for any analytic purpose. With a trusted data quality foundation and analytics-ready data, you can gain deeper insights, embed that knowledge into models, share new discoveries and automate decision-making processes to build a data-driven business.
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SAS
Published By: IBM     Published Date: Jul 05, 2018
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
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IBM
Published By: SAS     Published Date: Mar 06, 2018
For data scientists and business analysts who prepare data for analytics, data management technology from SAS acts like a data filter – providing a single platform that lets them access, cleanse, transform and structure data for any analytical purpose. As it removes the drudgery of routine data preparation, it reveals sparkling clean data and adds value along the way. And that can lead to higher productivity, better decisions and greater agility. SAS adheres to five data management best practices that support advanced analytics and deeper insights: • Simplify access to traditional and emerging data. • Strengthen the data scientist’s arsenal with advanced analytics techniques. • Scrub data to build quality into existing processes. • Shape data using flexible manipulation techniques. • Share metadata across data management and analytics domains.
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SAS
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Analysts struggle to incorporate new sources of data into their analysis because they rely on Microsoft Excel or other tools that were not designed for data blending. Deleting columns, parsing data, and writing complicated formulas to clean and combine data every time it changes is not an efficient way for today’s analysts to spend their time. Download The Definitive Guide to Data Blending and: Understand how analysts are empowered through data blending Learn how to automate time-consuming, manual data preparation tasks Gain deeper business insights in hours, not the weeks typical of traditional approaches
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Alteryx, Inc.
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: IBM     Published Date: Jul 06, 2016
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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ibm, ibm infosphere, big data, data optim, data management
    
IBM
Published By: IBM     Published Date: Apr 18, 2016
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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ibm, ibm infosphere, big data, data optim, data management
    
IBM
Published By: IBM     Published Date: Feb 22, 2016
IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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ibm, data, big data, integration, governance, iig, infosphere
    
IBM
Published By: Datawatch     Published Date: Dec 16, 2015
In this paper, the Top 10 Ways to Supercharge Analyst Productivity with Data Preparation, learn how a self-service data preparation solution saves analysts’ time by allowing them to manipulate, filter, enrich, blend and combine disparate data sets in a matter of minutes.
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data preparation, data wrangling, analyst productivity, data analysis, cleaning data, data blending
    
Datawatch
Published By: IBM     Published Date: Jul 08, 2015
While the term 'big data' has only recently come into vogue, IBM has designed solutions capable of handling very large quantities of data for decades. IBM InfoSphere Information Server is designed to help organizations understand, cleanse, monitor, transform and deliver data.
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IBM
Published By: SAS     Published Date: Apr 16, 2015
SAS Institute is gearing up to make a self-service data preparation play with its new Data Loader for Hadoop offering. Designed for profiling, cleansing, transforming and preparing data to load it into the open source data processing framework for analysis, Data Loader for Hadoop is a lynchpin in SAS's data management strategy for 2015. This strategy centers on three key themes: 'big data' management and governance involving Hadoop, the streamlining of access to information, and the use of its federation and integration offerings to enable the right data to be available, at the right time.
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SAS
Published By: Teradata     Published Date: Jan 16, 2015
NedTrain, a maintenance and cleaning service provider for locomotives, turns to Teradata Analytics for SAP® to unlock the valuable insight hidden in their newly implemented SAP® R/3 system. Impact and encourage positive end results...Download now!
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teradata, sap, maintenance, cleaning service provider, locomotives
    
Teradata
Published By: IBM     Published Date: Nov 19, 2014
According to a recent survey by the Compliance, Governance and Oversight Council, almost 70% of the electronic content and information organizations retain has no business or legal value. It’s simply digital detritus, retained because 1) we think we might need it sometime, 2) we forget about it, or 3) we don’t have policies and software in place to get rid of it. Ultimately, though, this unnecessary accumulation of content can create real problems in terms of e-discovery, regulation, management and cost. Watch this video white paper to learn more about: - How to get started on an information management strategy - The right combination of software and policy for successful information governance - The business case for proactive management of an organization’s digital footprint
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compliance, governance, oversight, digital debris, data cleanup, legacy data cleanup, information management, information management strategy, information governance
    
IBM
Published By: IBM     Published Date: Oct 22, 2014
A case study on how a major oil and gas producer saves 35 percent on data storage costs and 30 percent in litigation-related costs by adopting a smarter data discovery and defensible disposal strategy, using IBM Enterprise Content Management solutions.
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legacy data, data storage costs, data storage, content management
    
IBM
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