big data quality

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By: Collaborative Consulting     Published Date: Dec 23, 2013
There are some surprisingly straightforward reasons behind the glitches, delays, and cost-overruns that can bedevil data warehouse initiatives. ...The first is simply confusing expectations with requirements. But four other troublemakers can also lead to big problems for developers, IT departments, and organizations seeking to maximize the business value of information.
Tags : collaborative consulting, data warehouse, failed projects, business intelligence, business solution, meet expectations, big data, profile importance, cloud vendors, data quality, business goals, complicated architectures, avoid wasted expense, data management, data center
     Collaborative Consulting
By: Adobe     Published Date: Nov 07, 2013
Aberdeen's Insights provide the analyst's perspective on the research as drawn from an aggregated view of research surveys, interviews, and data analysis.
Tags : adobe, aberdeen group, analyst insight, technology tools, buying behavior, customer experience management, cem, buyer interactions, customer engagement programs, adobe customers outperform, company brand awareness, big data, structured data, data quality, data integration, customer segmentation, customer empowerment
     Adobe
By: Teradata     Published Date: May 02, 2017
Kylo overcomes common challenges of capturing and processing big data. It lets businesses easily configure and monitor data flows in and through the data lake so users have constant access to high-quality data. It also enhances data profiling while offering self-service and data wrangling capabilities.
Tags : cost reduction, data efficiency, data security, data integration, financial services, data discovery, data accessibility, data comprehension
     Teradata
By: IBM     Published Date: Jul 06, 2016
Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need.
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality, data integration, data center
     IBM
By: IBM     Published Date: Jul 08, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, idc, big data, data, analytics, information governance, knowledge management, data management, data center
     IBM
By: IBM     Published Date: Jan 19, 2017
The outcome of any big data analytics project, however, is only as good as the quality of the data being used. As big data analytics solutions have matured and as organizations have developed greater expertise with big data technologies he quality and trustworthiness of the data sources themselves are emerging as key concerns. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, analytics, ecm, data, big data, information governance, enterprise applications, data management, business technology
     IBM
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
By: Adverity     Published Date: Jun 15, 2018
A Beginner's Guide to Marketing Data Analytics Marketing Data is big & highly fragmented Big data is messy. It’s scattered across platforms, it’s diverse, and in its raw form, it’s practically unusable. We know, it’s a painful truth. The fact of the matter is that having a lot of data doesn’t necessarily mean that you have the answers to your most pressing questions. Looking for the most relevant bits in your pile of big data is like looking for a needle in a haystack. But don't you worry - we are here to help. This handy e-book will give you a short overview what quality matters, why data is so important and what you need to pay attention to. Best thing is: getting this ebook is super easy. Just fill out the form to the right and voilá - your download is ready. Enjoy this read!
Tags : marketing business intelligence, saas marketing optimization, measuring marketing performance, roi analytics, automated report generator, performance based marketing, online marketing data, roi metrics, marketing reports, roi reporting, reporting generator, automated reporting tool, marketing dashboard, marketing data, marketing intelligence, report software, marketing reporting, marketing metrics, performance marketing, marketing performance
     Adverity
By: SAS     Published Date: Sep 13, 2013
Insights from a webinar in the Applying Business Analytics webinar series.
Tags : sas, big data, big data quality, data, terabytes, petabytes, exabytes, software development
     SAS
By: IBM     Published Date: May 28, 2014
Read the whitepaper to find out how one client improved business value of their data by implementing InfoSphere Optim processes and technologies.
Tags : ibm, data lifecycle management, infosphere optim, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, lifecycle management
     IBM
By: IBM     Published Date: May 28, 2014
Different types of data have different data retention requirements. In establishing information governance and database archiving policies, take a holistic approach by understanding where the data exists, classifying the data, and archiving the data. IBM InfoSphere Optim™ Archive solution can help enterprises manage and support data retention policies by archiving historical data and storing that data in its original business context, all while controlling growing data volumes and improving application performance. This approach helps support long-term data retention by archiving data in a way that allows it to be accessed independently of the original application.
Tags : ibm, data retention, information governance, archiving, historical data, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence
     IBM
By: IBM     Published Date: Feb 24, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : big data, ibm, big data outcomes, information governance, big data analytics, it management, data management, data center
     IBM
By: IBM     Published Date: Apr 06, 2016
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments
Tags : ibm, big data, data security, risk management, security
     IBM
By: IBM     Published Date: Apr 18, 2016
"Built using the IBM® InfoSphere® Information Server, IBM BigInsights® BigIntegrate and BigInsights BigQuality provide the end-to-end information integration and governance capabilities that organizations need."
Tags : ibm, big data, ibm infosphere, ibm biginsights, ibm bigintegrate, ibm bigquality, data management, data quality, data integration
     IBM
By: IBM     Published Date: Jul 15, 2016
As big data environments ingest more data, organizations will face significant risks and threats to the repositories containing this data. Failure to balance data security and quality reduces confidence in decision making. Read this e-Book for tips on securing big data environments.
Tags : ibm, data, security, big data, data management
     IBM
By: IBM     Published Date: Oct 18, 2016
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : ibm, idc, big data, data, analytics, information governance, knowledge management, enterprise applications, data management, data center
     IBM
By: IBM     Published Date: Jan 09, 2014
According to Dr. Barry Devlin of 9sight Consulting, the truth behind all the talk about big data and the possibilities it can offer is not hard to see, provided that organizations are willing to return to the principles of good data management processes.
Tags : ibm, big data, 9sight consulting, data, it management, maximize business, deployment, business opportunities, big data usage, data warehouse, data center, business analytics, big data offerings, core business data, analytic data, puredata system, data virtualization, data integration, data types, data quality
     IBM
By: IBM     Published Date: Jul 13, 2015
This ebook explores how an enhanced 360-degree view of the customer optimizes and facilitates more personalized customer interactions.
Tags : customer centric organizations, crm, customer usability, personalized interactions, big data, data quality, data management
     IBM
By: IBM     Published Date: Apr 06, 2015
Big data analytics offer organizations an unprecedented opportunity to derive new business insights and drive smarter decisions. The outcome of any big data analytics project, however, is only as good as the quality of the data being used. Although organizations may have their structured data under fairly good control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. Good information governance is essential to the success of big data analytics projects. Good information governance also pays big dividends by reducing the costs and risks associated with the management of unstructured information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM's StoredIQ solution.
Tags : big data, analytics, unstructured content, enterprise information, ibm, security, it management, knowledge management, storage, data management
     IBM
By: IBM     Published Date: May 02, 2014
The end-to-end information integration capabilities of IBM® InfoSphere® Information Server are designed to help organizations understand, cleanse, monitor, transform and deliver data—as well as collaborate to bridge the gap between business and IT.
Tags : ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, it management, data management, data center
     IBM
By: IBM     Published Date: May 02, 2014
This eBookoutlines the best practices for data lifecycle management and how InfoSphere Optimsolutions enable organizations to support and implement them.
Tags : ibm, integrating big data, governing big data, integration, best practices, big data, ibm infosphere, it agility, performance requirements, hadoop, scalability, data integration, big data projects, high-quality data, leverage data replication, data persistence, virtualize data, lifecycle management, big data strategy, it management
     IBM
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