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• NoSQL database types explained: Column-oriented databases

  Learn about the uses of column-oriented databases and the large data model, data warehouses and high-performance querying benefits the NoSQL database brings to organizations. Continue Reading

• data lakehouse

  A data lakehouse is a data management architecture that combines the benefits of a traditional data warehouse and a data lake. Continue Reading

• How to choose exactly the right data story for your audience

  A data practitioner has two jobs: tell the right data story and in the right way to win over project stakeholders, data expert Larry Burns says in his latest book. Continue Reading

• Quiz: Test your understanding of the Hadoop ecosystem

  This quiz will test your knowledge of Hadoops basics including framework, capabilities and related technologies. Continue Reading

• stream processing

  Stream processing is a data management technique that involves ingesting a continuous data stream to quickly analyze, filter, transform or enhance the data in real time. Continue Reading

• Definitions to Get Started

  • data lakehouse
  • stream processing
  • columnar database
  • data modeling

  • relational database
  • Db2
  • big data management
  • big data

  View All Definitions

• 7 data modeling techniques and concepts for business

  Three types of data models and seven data modeling techniques are available to data management teams to convert mountains of information into valuable business intelligence.Continue Reading

• 9 steps to a dynamic data architecture plan

  Learn the nine steps to a comprehensive data architecture plan, including C-suite support, data personas, user needs, governance, catalogs, SWOT, lifecycles, blueprints and maps.Continue Reading

• How to build a successful cloud data architecture

  As enterprises vacate the premises and migrate their operations skyward, a cloud data architecture can provide the long-term flexibility to improve workflows, costs and security.Continue Reading

• columnar database

  A columnar database is a database management system (DBMS) that stores data in columns instead of rows.Continue Reading

• data modeling

  Data modeling is the process of documenting a complex software system design as an easily understood diagram, using text and symbols to represent the way data needs to flow.Continue Reading

• relational database

  A relational database is a collection of information that organizes data points with defined relationships for easy access.Continue Reading

• Db2

  Db2 is a family of database management system (DBMS) products from IBM that serve a number of different operating system (OS) platforms.Continue Reading

• big data management

  Big data management is the organization, administration and governance of large volumes of both structured and unstructured data.Continue Reading

• big data

  Big data is a combination of structured, semistructured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications.Continue Reading

• star schema

  A star schema is a database organizational structure optimized for use in a data warehouse or business intelligence that uses a single large fact table to store transactional or measured data, and one or more smaller dimensional tables that store ...Continue Reading

• data scrubbing (data cleansing)

  Data scrubbing, also referred to as data cleansing, is the process of amending or removing data in a database that is incorrect, incomplete, improperly formatted or duplicated.Continue Reading

• RFM analysis (recency, frequency, monetary)

  RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns.Continue Reading

• How to build an enterprise big data strategy in 4 steps

  Companies analyze vast stores of data to improve how they operate. Their efforts will bring diminishing returns, however, without a big data strategy. Here's how to build one.Continue Reading

• Big data collection processes, challenges and best practices

  Taming the infinite amount of data from multiple sources and deriving the greatest value to ensure trusted business decisions hinge on a foolproof system for collecting big data.Continue Reading

• 15 big data tools and technologies to know about in 2021

  Lots of tools are available to use in big data applications. Here's a look at the key features of 15 open source options to see if they fit your needs.Continue Reading

• denormalization

  Denormalization is the process of adding precomputed redundant data to an otherwise normalized relational database to improve read performance of the database.Continue Reading

• raw data (source data or atomic data)

  Raw data (sometimes called source data, atomic data or primary data) is data that has not been processed for use.Continue Reading

• Building a big data architecture: Core components, best practices

  To process the infinite volume and variety of data collected from multiple sources, most enterprises need to get with the program and build a multilayered big data architecture.Continue Reading

• data pipeline

  A data pipeline is a system that moves data from one (source) location to another (target) location, much like how an oil pipeline moves oil from one location to another.Continue Reading

• Establish big data integration techniques and best practices

  A big data integration strategy departs from traditional techniques, embraces several data processes working together and accounts for the volume, variety and velocity of data.Continue Reading

• Who belongs on a high-performance data governance team?

  Putting together a high-quality data governance team can be a challenge. Explore the necessary team members and best practices for a high-performing team.Continue Reading

• big data engineer

  A big data engineer is an information technology (IT) professional who is responsible for designing, building, testing and maintaining complex data processing systems that work with large data sets.Continue Reading

• NoSQL (Not Only SQL database)

  NoSQL is an approach to database management that can accommodate a wide variety of data models, including key-value, document, columnar and graph formats.Continue Reading

• How parallelization works in streaming systems

  Dive into this book excerpt from 'Grokking Streaming Systems' and learn the crucial role the parallelization process plays in the design of a streaming system.Continue Reading

• How a DataOps pipeline can support your data

  DataOps has created a lot of hype as a data management pipeline because of its focus on collaboration and flexibility. Read on to find out how these priorities support your data.Continue Reading

• 5 V's of big data

  The 5 V's of big data are the five main and innate characteristics of big data.Continue Reading

• data engineer

  A data engineer is an IT worker whose primary job is to prepare data for analytical or operational uses.Continue Reading

• What is a data warehouse analyst?

  Data warehouses aren't a new part of the data pipeline, but analyst roles to manage the repository are increasing. Here's a look at the role and responsibilities.Continue Reading

• Hadoop Distributed File System (HDFS)

  The Hadoop Distributed File System (HDFS) is the primary data storage system used by Hadoop applications.Continue Reading

• Open source database migration guide: How to transition

  Open source database transitions have been on the rise as they prove to be worthy competitors to commercial database options, but that transition requires strategy and user buy-in.Continue Reading

• Why your data story matters and how to tell it

  Data storytelling isn't just for business analysts. Find out how to build a data management story and why you need to have one in the first place.Continue Reading

• Creating a data advantage by building a data ecosystem

  Developing a data ecosystem will improve personalization and customer retention. Find out how data mining across channels can build a data advantage for your organization.Continue Reading

• Enterprise data lakes hold the key to actionable insights

  Technological pillars of sound business decisions, AI, machine learning and advanced analytics depend on the quantity, quality and integrity of information in data lakes.Continue Reading

• Graph database vs. relational database: Key differences

  Relational databases and graph databases both focus on the relationships between data but not in the same ways. Here are some key differences between the two.Continue Reading

• feature engineering

  Feature engineering is the process that takes raw data and transforms it into features that can be used to create a predictive model using machine learning or statistical modeling, such as deep learning.Continue Reading

• DBMS keys: Primary, super, foreign and candidate keys with examples

  Here's a guide to primary, super, foreign and candidate keys, what they're used for in relational database management systems and the differences among them.Continue Reading

• SQL (Structured Query Language)

  SQL (Structured Query Language) is a standardized programming language that's used to manage relational databases and perform various operations on the data in them.Continue Reading

• Top 5 U.S. open data use cases from federal data sets

  The U.S. government has made data sets from many federal agencies available for public access to use and analyze. Check out some of the ways that data is being used.Continue Reading

• Quiz on MongoDB 4 new features and database updates

  Check out this excerpt from the new book Learn MongoDB 4.x from Packt Publishing, then quiz yourself on new updates and features to the database.Continue Reading

• Google BigQuery

  Google BigQuery is a cloud-based big data analytics web service for processing very large read-only data sets.Continue Reading

• Why understanding data structures is so important to coders

  Jay Wengrow talks about how his new book on data structures and algorithms and considerations for making your choices as efficient as possible.Continue Reading

• Key steps in the feature engineering process

  Feature engineering is key to machine learning algorithms. Read on to learn how those features are created and chosen to increase the accuracy of those models.Continue Reading

• data analytics (DA)

  Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain.Continue Reading

• Apache Hadoop YARN

  Apache Hadoop YARN is the resource management and job scheduling technology in the open source Hadoop distributed processing framework.Continue Reading

• MongoDB

  MongoDB is an open source NoSQL database management program. NoSQL is used as an alternative to traditional relational databases.Continue Reading

• How to ensure your data lake security

  Your data lake is full of sensitive information and securing that data is a top priority. These are the best practices to keep that information safe from hackers.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

• Developing an enterprise data strategy: 10 steps to take

  Consultants detail 10 to-do items for data management teams looking to create a data strategy to help their organization use data more effectively in business operations.Continue Reading

• database replication

  Database replication is the frequent electronic copying of data from a database in one computer or server to a database in another -- so that all users share the same level of information.Continue Reading

• What is data governance and why does it matter?

  Data governance (DG) is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage.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

• data stewardship

  Data stewardship is the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner.Continue Reading

• consumer privacy (customer privacy)

  Consumer privacy, also known as customer privacy, involves the handling and protection of the sensitive personal information provided by customers in the course of everyday transactions.Continue Reading

• corporate performance management (CPM)

  Corporate performance management (CPM) is a term used to describe the various processes and methodologies involved in aligning an organization's strategies and goals to its plans and executions in order to control the success of the company.Continue Reading

• Extract, Load, Transform (ELT)

  Extract, Load, Transform (ELT) is a data integration process for transferring raw data from a source server to a data system (such as a data warehouse or data lake) on a target server and then preparing the information for downstream uses.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

• 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

• database as a service (DBaaS)

  Database as a service (DBaaS) is a cloud computing managed service offering that provides access to a database without requiring the setup of physical hardware, the installation of software or the need to configure the database.Continue Reading

• data integration

  Data integration is the process of combining data from multiple source systems to create unified sets of information for both operational and analytical uses.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

• master data management (MDM)

  Master data management (MDM) is a process that creates a uniform set of data on customers, products, suppliers and other business entities from different IT systems.Continue Reading

• data quality

  Data quality is a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability and whether it's up to date.Continue Reading

• data classification

  Data classification is the process of organizing data into categories that make it is easy to retrieve, sort and store for future use.Continue Reading

• What is data management and why is it important?

  Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process.Continue Reading

• Hadoop

  Hadoop is an open source distributed processing framework that manages data processing and storage for big data applications running in clustered systems.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

• T-SQL (Transact-SQL)

  T-SQL (Transact-SQL) is a set of programming extensions from Sybase and Microsoft that add several features to the Structured Query Language (SQL), including transaction control, exception and error handling, row processing and declared variables.Continue Reading

• Entity Relationship Diagram (ERD)

  An entity relationship diagram (ERD), also known as an entity relationship model, is a graphical representation that depicts relationships among people, objects, places, concepts or events within an information technology (IT) system.Continue Reading

• database (DB)

  A database is a collection of information that is organized so that it can be easily accessed, managed and updated.Continue Reading

• data

  In computing, data is information that has been translated into a form that is efficient for movement or processing.Continue Reading

• data warehouse

  A data warehouse is a federated repository for all the data collected by an enterprise's various operational systems, be they physical or logical.Continue Reading

• Big data containers gain wider appeal in system deployments

  This handbook examines the use of Docker containers in Kubernetes clusters to run big data systems and offers insight on container deployment and management issues.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

• Microsoft SQL Server

  Microsoft SQL Server is a relational database management system, or RDBMS, that supports a wide variety of transaction processing, business intelligence and analytics applications in corporate IT environmentsContinue Reading

• Data as a Service (DaaS)

  Data as a Service (DaaS) is an information provision and distribution model in which data files (including text, images, sounds, and videos) are made available to customers over a network, typically the Internet.Continue Reading

• Advice on enterprise data cleansing from an SAP VP

  SAP's Kristin McMahon details data cleansing best practices and explains why a good data cleanse needs continual communication, collaboration and oversight.Continue Reading

• DataOps (data operations)

  DataOps (data operations) is an Agile approach to designing, implementing and maintaining a distributed data architecture that will support a wide range of open source tools and frameworks in production. The goal of DataOps is to create business ...Continue Reading

• data virtualization

  Data virtualization is an umbrella term used to describe any approach to data management that allows an application to retrieve and manipulate data without needing to know any technical details about the data such as how it is formatted or where it ...Continue Reading

• Data model design tips to help standardize business data

  Data models should be understandable to business users and kept to a reasonable scope, say the leaders of a data modeling initiative at England's Environment Agency.Continue Reading

• USA Patriot Act

  The USA Patriot Act is a law enacted in 2001, granting new and extended data-collection abilities to federal agencies in an effort to combat terrorism after the September 11 attacks.Continue Reading

• USAA adds data engineering skills to speed data science work

  When the United Services Automobile Association's data science team wasn't getting data in the right format, the team lead realized the USAA needed more data engineers.Continue Reading

• data profiling

  Data profiling is the process of examining, analyzing and reviewing data to collect statistics surrounding the quality and hygiene of the dataset.Continue Reading

• 5 things to know about deploying big data systems in data containers

  Planning for security and container APIs, and watching out for infrastructure sprawls are some issues to be aware of before deploying big data in containers.Continue Reading

• DataOps is more than DevOps for data, Delphix CTO says

  Data operations is young compared to DevOps, but it is increasingly used as part of projects that put data at the center of development. Here, Delphix CTO Eric Schrock makes observations about the trend.Continue Reading

• HR makes major strides toward improving employee engagement

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• What is the difference between DBMS and RDBMS?

  A relational database management system is the most popular type of database management system for business uses. Find out how RDBMS software differs from DBMS technology in general.Continue Reading

• SQL vs. NoSQL: What do you know about the database designs?

  The decision to use a SQL database or a NoSQL database can be made wisely only if the ins and outs of both are understood. See how well you know the database architectures.Continue Reading

• data mart (datamart)

  A data mart is a repository of data that is designed to serve a particular community of knowledge workers.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

• AI for analytics augments and bolsters business intelligence

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• What is an enterprise data strategy?

  Defining a data strategy can help focus an organization's data management initiatives -- but it isn't the same as data governance. Expert Anne Marie Smith explains why.Continue Reading

• customer data integration (CDI)

  Customer data integration (CDI) is the process of defining, consolidating and managing customer information across an organization's business units and systems to achieve a "single version of the truth" for customer data.Continue Reading

• 5 to-dos for your GDPR compliance checklist

  It's never too late to fine-tune your GDPR strategy. Expert Anne Marie Smith suggests a current state analysis of your PII protections, drafting a data privacy policy and more.Continue Reading

• Cloud vs. legacy ERP systems: Tug of war intensifies for SMBs

  Aging legacy ERP systems at SMBs seem to be getting plenty of scrutiny these days. Heightened consumer demands, shifting technology landscapes and relentless market disruptions, not to mention maintenance costs, technical support and obsolescence, ...Continue Reading