In computing, a data warehouse, also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is considered a core component of business intelligence. Data warehouses are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. This is beneficial for companies as it enables them to interrogate and draw insights from their data and make decisions.
In computing, extract, transform, load (ETL) is a three-phase process where data is extracted, transformed and loaded into an output data container. The data can be collated from one or more sources and it can also be output to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on reccurring schedules either as single jobs or aggregated into a batch of jobs.
Data migration is the process of selecting, preparing, extracting, and transforming data and permanently transferring it from one computer storage system to another. Additionally, the validation of migrated data for completeness and the decommissioning of legacy data storage are considered part of the entire data migration process. Data migration is a key consideration for any system implementation, upgrade, or consolidation, and it is typically performed in such a way as to be as automated as possible, freeing up human resources from tedious tasks. Data migration occurs for a variety of reasons, including server or storage equipment replacements, maintenance or upgrades, application migration, website consolidation, disaster recovery, and data center relocation.
Data integration involves combining data residing in different sources and providing users with a unified view of them. This process becomes significant in a variety of situations, which include both commercial and scientific domains. Data integration appears with increasing frequency as the volume, complexity and the need to share existing data explodes. It has become the focus of extensive theoretical work, and numerous open problems remain unsolved. Data integration encourages collaboration between internal as well as external users. The data being integrated must be received from a heterogeneous database system and transformed to a single coherent data store that provides synchronous data across a network of files for clients. A common use of data integration is in data mining when analyzing and extracting information from existing databases that can be useful for Business information.
IBM Netezza is a subsidiary of American technology company IBM that designs and markets high-performance data warehouse appliances and advanced analytics applications for uses including enterprise data warehousing, business intelligence, predictive analytics and business continuity planning.
A virtual private cloud (VPC) is an on-demand configurable pool of shared resources allocated within a public cloud environment, providing a certain level of isolation between the different organizations (denoted as users hereafter) using the resources. The isolation between one VPC user and all other users of the same cloud (other VPC users as well as other public cloud users) is achieved normally through allocation of a private IP subnet and a virtual communication construct (such as a VLAN or a set of encrypted communication channels) per user. In a VPC, the previously described mechanism, providing isolation within the cloud, is accompanied with a virtual private network (VPN) function (again, allocated per VPC user) that secures, by means of authentication and encryption, the remote access of the organization to its VPC resources. With the introduction of the described isolation levels, an organization using this service is in effect working on a 'virtually private' cloud (that is, as if the cloud infrastructure is not shared with other users), and hence the name VPC.
Apache Pig is a high-level platform for creating programs that run on Apache Hadoop. The language for this platform is called Pig Latin. Pig can execute its Hadoop jobs in MapReduce, Apache Tez, or Apache Spark. Pig Latin abstracts the programming from the Java MapReduce idiom into a notation which makes MapReduce programming high level, similar to that of SQL for relational database management systems. Pig Latin can be extended using user-defined functions (UDFs) which the user can write in Java, Python, JavaScript, Ruby or Groovy and then call directly from the language.
OpenShift is a family of containerization software products developed by Red Hat. Its flagship product is the OpenShift Container Platform — a hybrid cloud platform as a service built around Linux containers orchestrated and managed by Kubernetes on a foundation of Red Hat Enterprise Linux. The family's other products provide this platform through different environments: OKD serves as the community-driven upstream, Several deployment methods are available including self-managed, cloud native under ROSA, ARO and RHOIC on AWS, Azure, and IBM Cloud respectively, OpenShift Online as software as a service, and OpenShift Dedicated as a managed service.
Apache Drill is an open-source software framework that supports data-intensive distributed applications for interactive analysis of large-scale datasets. Built chiefly by contributions from developers from MapR, Drill is inspired by Google's Dremel system. Drill is an Apache top-level project. Tom Shiran is the founder of the Apache Drill Project. It was designated an Apache Software Foundation top-level project in December 2016.
Cloud analytics is a marketing term for businesses to carry out analysis using cloud computing. It uses a range of analytical tools and techniques to help companies extract information from massive data and present it in a way that is easily categorised and readily available via a web browser.
SAP HANA is an in-memory, column-oriented, relational database management system developed and marketed by SAP SE. Its primary function as the software running a database server is to store and retrieve data as requested by the applications. In addition, it performs advanced analytics and includes extract, transform, load (ETL) capabilities as well as an application server.
A data lake is a system or repository of data stored in its natural/raw format, usually object blobs or files. A data lake is usually a single store of data including raw copies of source system data, sensor data, social data etc., and transformed data used for tasks such as reporting, visualization, advanced analytics and machine learning. A data lake can include structured data from relational databases, semi-structured data, unstructured data and binary data. A data lake can be established "on premises" or "in the cloud".
Presto is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, and allows use of multiple data sources within a query. Presto is community-driven open-source software released under the Apache License.
Function as a service (FaaS) is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage application functionalities without the complexity of building and maintaining the infrastructure typically associated with developing and launching an app. Building an application following this model is one way of achieving a "serverless" architecture, and is typically used when building microservices applications.
Data blending is a process whereby big data from multiple sources are merged into a single data warehouse or data set.
Kyvos is a business intelligence acceleration platform for cloud and big data platforms developed by an American privately held company named Kyvos Insights. The company, headquartered in Los Gatos, California, was founded by Praveen Kankariya, CEO of Impetus Technologies. The software provides OLAP-based multidimensional analysis on big data and cloud platforms and was launched officially in June 2015. In December the same year, the company was listed among the 10 Coolest Big Data Startups of 2015 by CRN Magazine.
Azure Data Explorer is a fully-managed big data analytics cloud platform and data-exploration service, developed by Microsoft, that ingests structured, semi-structured and unstructured data. The service then stores this data and answers analytic ad hoc queries on it with seconds of latency. It is a full text indexing and retrieval database, including time series analysis capabilities and regular expression evaluation and text parsing.
AWS Glue is an event-driven, serverless computing platform provided by Amazon as a part of Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. It was introduced in August 2017.
Power Query is an ETL tool created by Microsoft for data extraction, loading and transformation, and is used to retrieve data from sources, process it, and load them into one or more target systems. Power Query is available in several variations within the Microsoft Power Platform, and is used for business intelligence on fully or partially self-service platforms. It is found in software such as Excel, Power BI, Analysis Services, Dataverse, Power Apps, Azure Data Factory, SSIS, Dynamics 365, and in cloud services such as Microsoft Dataflows, including Power BI Dataflow used with the online Power BI Service or the somewhat more generic version of Microsoft Dataflow used with Power Automate.
HammerDB is an open source database benchmarking application developed by Steve Shaw. HammerDB supports databases such as Oracle, SQL Server, Db2, MySQL and MariaDB. HammerDB is written in TCL and C, and is licensed under the GPL v3.
