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Learn to apply best practices and optimize your operations.
Manage
Learn to apply best practices and optimize your operations.
Cloud data catalog benefits for the enterprise
Vendor cloud data catalog options are expanding and offering more automated tools to end users. Read on to find out how enterprises can benefit from these options. Continue Reading
Pandemic exposes difficulty of data management in education
Limited resources and a shift to remote learning have shown the inequalities across school districts when it comes to data management and the negative impact this can have. Continue Reading
Data lineage documentation imperative to data quality
Understanding the detailed journey of data elements throughout the data pipeline can help an enterprise maintain data quality and improve trustworthiness. Continue Reading
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Data anonymization best practices protect sensitive data
See how data anonymization best practices can help your organization protect sensitive data and those who could be at risk if that data identified them. Continue Reading
Maintaining data integrity key for data quality
Maintaining data integrity through improved communication and data literacy is paramount for organizations in the enterprise seeking to ensure data quality and trust. Continue Reading
Investment in talent key for data quality in healthcare
Investing in training employees on proper data gathering and management practices is crucial for healthcare organizations seeking to ensuring data quality and patient care.Continue Reading
Should you host your database on-site or in the cloud?
There's been a surge of movement to the cloud in recent years, but there are still some benefits to an on-site database. Read on for a comparison of on-site and cloud platforms.Continue Reading
Top 5 feature engineering tips for better models
From understanding a model's expected goal to factoring in subject matter expertise, experts talk about the best ways to improve your feature engineering.Continue Reading
Key points for a monitoring center pandemic action plan
On-site monitoring centers come under stress when it's necessary for most workers to telecommute. Here are key points to include in a crisis plan to continue service availability.Continue Reading
Surprising insight on the data governance process
Many enterprise data governance processes have been around for a while. Read on for ways a modern approach can be beneficial, and preview a new book that can update your strategy.Continue Reading
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Data integration technologies unify multiple data stores
Manual data integration can still benefit small and medium businesses, but a prolonged manual process can slow and detract from actionable work by data professionals.Continue Reading
Organization and automation ease data preparation process
By laying down proper groundwork and investing in automated checks, companies can ease the data preparation process and ensure they are getting the most out of their data.Continue Reading
Big data security management embraces governance, privacy
Cyberattacks, GDPR and CCPA compliance, and COVID-19 present serious security and privacy challenges for managers tasked with protecting their data stores.Continue Reading
GDPR, CCPA, cloud drive security management tool makeovers
As data protection and privacy laws like GDPR and CCPA take hold, data managers refine governance practices, while vendors enhance traditional big data security tools.Continue Reading
Building a strong data analytics platform architecture
A strong analytics platform is key to meeting demands in a data-driven business. Read on for the key components your platform architecture should include.Continue Reading
When a DIY database management system design is the best fit
Learn how a combination of homegrown, off-the-shelf and open source tools, plus proper motivation, can yield a DIY DBMS that meets corporate expectations, needs and ROI.Continue Reading
Building a database application the DIY way
Business users experience the trials, tribulations and exultations of building a DIY DBMS, especially when IT expertise is not readily available or costs are too high.Continue Reading
Using DataOps to create business value from big data
Now is the time to take all that data your organization has amassed through the years and, with DataOps, use it to make actionable business decisions.Continue Reading
How to build an effective streaming data architecture
Data architecture can be tricky when it comes to real-time analytics. Clear objectives and scalability are important factors when determining the streaming data architecture you need.Continue Reading
What steps are key to building a data catalog?
An enterprise data catalog can help data stewards and other users in an organization manage metadata and explore data assets. Here are 10 key steps for creating a data catalog.Continue Reading
6 best practices on data governance for big data environments
Efforts to govern big data must corral a mix of structured and unstructured data. That's a challenge for most organizations. These six action items will help.Continue Reading
5 benefits of building a strong data governance strategy
Effective data governance provides a variety of benefits to organizations, including improvements in operational efficiency, data quality and business decision-making.Continue Reading
Data governance roles and responsibilities: What's needed
Data governance requires a team effort. Experts offer advice on how to structure and implement data governance roles that engage business users across the enterprise.Continue Reading
Should you host your data lake in the cloud?
On premises or in the cloud: What's the better place for your data lake? Here are some things to consider before deciding where to deploy a big data environment.Continue Reading
How data lineage tools boost data governance policies
Organizations can bolster data governance efforts by tracking the lineage of data in their systems. Get advice on how to do so and key features in data lineage tools.Continue Reading
Proactive practices for data quality improvement
Instead of waiting for data quality to become an issue, consider a proactive approach. Here are ways to improve data quality in your organization before it's a problem.Continue Reading
Data warehousing design and value change with the times
Big data, the cloud and analytics profoundly shape data warehouse purpose and design. Learn how companies derive value from a repository that at times needs definition.Continue Reading
Analytics demands add loftier goals to data warehouse strategies
As the concept of storing data and the technologies needed to do it evolve, companies with set goals in mind are building their data warehouses to maximize analytics outcomes.Continue Reading
How to improve data governance for self-service analytics
Citizen data scientists and self-service analytics are on the rise as the data scientist shortage continues. Here are some data management best practices to support them.Continue Reading
Data catalog best practices rely on teamwork, governance, tools
This handbook provides advice on creating data catalogs to help data analysts and other users find information in corporate systems, plus insight on data catalog trends.Continue Reading
Data catalog management for analytics fraught with unique demands
Data catalogs for analytics applications demand detailed assessment of user needs, cross-functional teams, ready access, continuous improvement and a self-sustaining system.Continue Reading
Data warehouse technologies evolve as vendors look skyward
The need for high-speed analytics and low latency are pushing data warehousing vendors to create and reinvent their platforms and, in some cases, reinvent themselves.Continue Reading
How to streamline feature engineering for machine learning
Structured data is necessary in machine learning, but sifting through data is time consuming. Streamlining the feature engineering process can help data scientists be more productive.Continue Reading
Top database cloud migration considerations for enterprises
Many organizations are switching to cloud databases and big data platforms. But understanding what option best meets your data needs is an important first step.Continue Reading
Managing unstructured data is crucial to enterprises' AI goals
Unstructured data makes up a huge portion of most businesses' data volume. But, with data-hungry AI systems coming online, making sense of these stores has never been more important.Continue Reading
RDBMS (relational database management system)
A relational database management system (RDBMS) is a collection of programs and capabilities that enable IT teams and others to create, update, administer and otherwise interact with a relational database.Continue Reading
How enterprises navigate GDPR data management rules
For businesses that operate in the EU, complying with GDPR has to be a top priority. And in many, much of the compliance burden falls on the data management staff.Continue Reading
5 steps to an improved data quality assurance plan
Consultant David Loshin offers tips on developing a data quality strategy that can help identify data errors before they cause big business problems.Continue Reading
DOD CDO shares 7 data management best practices
The DOD's first chief data officer, Michael Conlin, shares tips on how organizations can modernize their data management practices with the objective of matching private enterprise.Continue Reading
Align business and IT drivers through data quality best practices
Information management consultants talk about the importance of aligning business and IT drivers for a holistic architectural approach to ensuring strong data quality.Continue Reading
Third-party database tools boast attractive alternatives
For companies considering third-party database tools, this handbook provides expert advice on evaluating and deploying on-premises and cloud options from third parties.Continue Reading
Database management tools from third parties make natives restless
Third-party database performance tools offer attractive alternatives to management software from DBMS vendors, provided their capabilities include orchestration, governance and integration.Continue Reading
GDPR, AI intensify privacy and data protection compliance demands
This guide covers the challenges data management teams face on data protection and privacy, particularly with the rise of GDPR and similar laws and the growing use of AI tools.Continue Reading
Information Builders exec talks data management ethics
In this Q&A, James Cotton, director of the Data Management Centre of Excellence at Information Builders, offers advice on how organizations can carry out ethical data management.Continue Reading
Data modeling techniques to overcome common business challenges
In this interview, author and data modeling instructor Steve Hoberman discusses techniques for dealing with challenges that may arise in the data modeling process.Continue Reading
How 4 organizations are breaking down data silos
Siloed data continues to inhibit enterprise efficiency. Here, IT professionals discuss problems their organizations are facing around data silos -- and how they're solving them.Continue Reading
Building leaner, meaner BI data sources
As business intelligence analysis and reporting platforms become increasingly important in the enterprise, so does the data that feeds them. Are your BI data sources up to par?Continue Reading
Data virtualization tools promote anywhere, anytime data access
This online handbook examines data virtualization software and how organizations are deploying and using the technology as part of their data integration processes.Continue Reading
Data virtualization benefits seen in unified views, IT agility
Through in-place integration, data virtualization platforms can provide wider access to data and simplify security and governance. But they come with some limitations.Continue Reading
Data virtualization layer feeds logical data warehouse, Agile BI
Indiana University is using data virtualization to combine data from various source systems for analysis, as part of an initiative to improve strategic decision-making.Continue Reading
Data modeling best practices power analytics, business apps
Data modeling is a key part of data management and analytics. This handbook highlights best practices for creating data models and new functionality in modeling tools.Continue Reading
How data staging helped Walgreens transform its supply chain
Walgreens built a centralized data warehouse to give supply chain partners a better view into its data -- but analytics were slow. That's where a data staging tier came in.Continue Reading
How to navigate the challenges of the data modeling process
Data modeling and curation can help businesses more efficiently use data they've collected. There are challenges, however -- beginning with ensuring data quality.Continue Reading
8 tips to improve the data curation process
A data curation and modeling strategy can ensure accuracy and enhance governance. Experts offer eight best practices for curating data. First, start at the source.Continue Reading
5 best practices for managing real-time data integration
Real-time data integration isn't like traditional data integration -- "it's moving, it's dirty and it's temporal," cautions one data pro. Experts offer up some best practices.Continue Reading
Why organizations need a solid data governance strategy
The flood of data flowing into data warehouses, data lakes and other systems makes effective data governance a must for successful business analytics initiatives.Continue Reading
Data management trends for 2019: Governance, DataOps, cloud
Better data governance, increased cloud use and wider DataOps adoption head the list of trends for data management teams to plan for in 2019, IT analysts say.Continue Reading
How data duplication in healthcare is diagnosed
Electronic health record systems have helped reduce duplicate patient data in hospitals -- but they haven't cured the problem. Find out how organizations are addressing the issue.Continue Reading
How to build a master data index: Static vs. dynamic indexing
Expert David Loshin explores the differences between static and dynamic indexing in master data management systems, and which queries each approach can support.Continue Reading
How deterministic and probabilistic matching work
Expert David Loshin explores the benefits and challenges of the two classes of record matching in master data management systems: deterministic matching vs. probabilistic matching.Continue Reading
11 features to look for in data quality management tools
As the need for quality data has increased, so have the capabilities of data quality tools. Learn how collaboration, data lineage and other features enable data quality.Continue Reading
Big data platform broadens place in analytics architecture
Big data platforms stumbled a bit getting out of the prototyping stage. But a view from the Strata Data Conference in New York sees broader use in the offing.Continue Reading
The gradual evolution of master data management software
Master data management began with a bang, then hit roadblocks due to complexity. Now, MDM is shifting toward more pragmatic projects tied to data governance.Continue Reading
Mining equipment maker uses BI on Hadoop to dig for data
BI on Hadoop is still new, but moving BI to data is trending. A data scientist working with IoT data at Komatsu sees the importance of getting big data to the right people.Continue Reading
What is the best structure for data governance programs?
The optimal approach to a data governance framework includes a program team, a data governance council and stewards. Expert Anne Marie Smith explains what role each group plays.Continue Reading
Why data quality tools matter in today's organizations
Data is everywhere -- but is it good? Data quality tools could answer that question and help save time and money. So why don't more organizations use the technology?Continue Reading
GDPR checklist items data managers might have overlooked
Now that the General Data Protection Regulation has been implemented, it's a good time for organizations to make sure they haven't missed any GDPR best practices.Continue Reading
How to manage data and the GDPR right to be forgotten
The General Data Protection Regulation requires organizations to delete personally identifiable information if customers ask -- which can be a challenge. Experts offer four tips.Continue Reading
How graph data modeling can help evaluate database tools
Mapping data to a graph model can be challenging, but these steps can help you create prototype applications -- which then can aid in evaluating graph databases.Continue Reading
When to choose an S3 big data environment over HDFS storage
Selecting a storage service for big data in the cloud can be challenging. Expert David Loshin explains usage patterns that could lead organizations to Amazon Simple Storage Service.Continue Reading
Four first steps for customer data management
Forrester's Mike Gualtieri details how to develop a unified plan to manage customer data that gives business users what they need to manage CRM programs.Continue Reading
Evolving data integration strategies target new analytics needs
Most companies don't have a shortage of data, but it's often stored in siloed systems or inconsistent formats -- problems that data integration programs need to address.Continue Reading
What goes into a customer analytics data integration framework
Customer data integration is a minefield for IT teams to navigate. But incorporating a set of core technical functions into an integration architecture can ease the process.Continue Reading
Six data risk management steps for GDPR compliance
By layering data risk management processes into your data governance framework, you can ensure the personally identifiable information your company stores meets GDPR compliance rules.Continue Reading
CockroachDB database wagered on for scalability boost, GDPR
CockroachDB is an open source distributed database designed for processing on a global scale, a need that online gambling company Kindred Group hopes it can meet.Continue Reading
relational database management system
A relational database management system (RDBMS) is a collection of programs and capabilities that enable IT teams and others to create, update, administer and otherwise interact with a relational database.Continue Reading
GDPR data protection edicts make good data governance a must
The European Union's new GDPR law puts the onus on companies to ensure that their data governance and management practices enable them to comply with its requirements.Continue Reading
GDPR rules can spur broader steps to protect sensitive data
Companies need to make compliance with GDPR's requirements on managing personal data a priority, but they should also work to implement wider data protection efforts in the future.Continue Reading
Security of big data fashions a whole new look with GDPR
As data managers scramble to protect their precious lakes of washed and unwashed data from the evils of hacking, malware, ransomware and botnets, there comes a privacy regulation of European Union origin that could change the way many U.S. companies...Continue Reading
IoT, edge computing spawn new security issues
As real-time big data increasingly hitches up to internet of things, edge computing power and fog nodes, a whole new layer of security threats emerges.Continue Reading
IT teams take big data security issues into their own hands
Data security needs to be addressed upfront in deployments of big data systems -- and users are likely to find they have to build some security capabilities themselves.Continue Reading
Information architecture applied to big data streaming, AI
New technologies challenge data professionals, but taking a step back helps with hurdles. In this interview, consultant William McKnight takes a measured look at data streaming, GDPR and AI.Continue Reading
Cloud workloads, data lakes challenge information architecture
Data management options are expanding; cloud workloads are an example. That means changing your approach to information architecture, says data management expert William McKnight.Continue Reading
GDPR mandates push data quality improvement into IT spotlight
Data quality issues cost companies significant amounts of money in lost revenue and added expenses, and their impact will only get bigger when the EU starts enforcing its GDPR law.Continue Reading
IT, others focus efforts as GDPR implementation date looms
The EU's General Data Protection Regulation is meant to bring better data privacy to bear in the age of big data. How GDPR implementation will proceed remains to be seen.Continue Reading
Data expert: GDPR deadline is an opportunity, not a burden
There is stress as the EU's General Data Protection Regulation compliance deadline nears, but the GDPR privacy movement is a good thing for data policies, advises consultant Daragh O Brien.Continue Reading
Data lake concept needs firm hand to pay big data dividends
Data lakes pose technology deployment and data management challenges that can leave analytics users high and dry if the implementation process isn't handled properly.Continue Reading
Data analytics architecture must break down higher ed silos
Siloed data isn't only a problem for businesses. It's also a big issue for many large universities -- one that their data infrastructures need to resolve for effective analytics.Continue Reading
Data catalog software takes open data initiative to the streets
Data catalog software from Alation helped San Diego's chief data officer open up the city's data to residents, as well as city planners and other government workers.Continue Reading
Data managers should study up on GPU deep learning
As GPU deep learning becomes more common, data managers will have to navigate several new layers of complexity in their quest to build or buy suitable data infrastructure.Continue Reading
Expert: For BI, you must know the data integration process
Understanding the data integration process is central to self-service BI and data architecture design, consultant Rick Sherman says in an end-of-year look at data management trends.Continue Reading
Analytics uses drive need for speed in working with big data
Today, analytics work is about speed. That means rapidly building clusters and transforming and querying data. Learn how users are streamlining digital business.Continue Reading
Make data usability a priority on data quality for big data
To help make big data analytics applications more effective, IT teams need to augment conventional data quality processes with measures aimed at improving data usability for analysts.Continue Reading
Big data systems up ante on data quality measures for users
At the Strata conference in New York, IT managers detailed steps they're taking to improve data quality in their big data environments in order to help ensure analytics accuracy.Continue Reading
Managing the big data ecosystem requires agility amid disruptions
In some regards, the term big data management can be viewed as an oxymoron. In fact, oxymorons abound in this industry and society -- virtual reality, artificial intelligence, science fiction and awfully good, the ...Continue Reading
Machine learning, IoT bring big changes to data management systems
Companies are using big data systems, deep learning and machine learning techniques to drive software advances. To go even further, their data management systems must also evolve.Continue Reading
From all the data chaos emerges big data value
Businesses spend millions of dollars to collect, mine, prep and analyze data to gain an edge in the marketplace. Yet, they have a hard time determining big data's actual value.Continue Reading
A strong metadata management process eases big data woes
Big data often comes with big data management problems. Clean, well-defined metadata can make the difference in analyzing big data and delivering actionable business intelligence.Continue Reading
Big data systems help companies build new business strategies
Organizations hungry for more revenue are using Hadoop and other big data technologies to break their existing business molds and pursue new strategies and product offerings.Continue Reading
Machine learning algorithms meet data governance
Machine learning algorithms may change computing, but they're a bit of a black box. Still, there are ways to tame them with flexible data governance, according to tech startup exec Andrew Burt.Continue Reading