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matched with a corresponding tuple from the right relation ( q ) based on the join condition or augmented with null values in case no match with a tuple from q can be made. a left outer join can be represented as. a right outer join includes all tuples from the right relation ( q ) in the result, either matched with a ... | openstax_introduction_to_computer_science_-_web | [
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the attribute type of which the value needs to be retrieved, and 382 8 • data management access for free at openstax. org cond ( t ) the range relation and extra conditions to select relevant tuples. consider the following example : { t. studentid, t. studentname | student ( t ) and t. studentprogram = 3 } a condition ... | openstax_introduction_to_computer_science_-_web | [
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follows : { ab | ( e ) ( student ( abcde ) and e = 3 ) } in this case, we defined five domain variables as a for the domain of studentid, b for the domain of studentname, c for the domain of studentaddress, d for the domain of studentcity, and e for the domain of studentprogram. the condition e = 3 is a selection condi... | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 383 technology in everyday life rdbms airplanes have to be designed and tested for safety. airplane wings are complex items that include a large number of parts, come in various shapes and forms ( e. g., rectangular wings for small airplane, elliptical wings, tapered wings ... | openstax_introduction_to_computer_science_-_web | [
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##ructuring a relational database to reduce data redundancy and improve data integrity is called database normalization. a normal form applies to a table / relation, not to the database. the main types of normalization are • first normal form ( 1nf ), • second normal form ( 2nf ), • third normal form ( 3nf ), • boyce -... | openstax_introduction_to_computer_science_-_web | [
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name item 1 item 2 shirl adam milk bread jeff mark juice water rana park bread milk table 8. 4 table converted to 1nf first name last name item shirl adam milk shirl adam bread jeff mark juice jeff mark water rana park bread rana park milk table 8. 5 table converted to 2nf customer id first name last name 1 shirl adam ... | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 385 item id item 1 milk 2 bread 3 juice 4 water table 8. 7 table converted to 3nf : item customer id item id 1 1 1 2 2 3 2 4 table 8. 8 table converted to 3nf : relational table relational database design modeling data into a set of tables with rows and columns is called re... | openstax_introduction_to_computer_science_-_web | [
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##nary, and more generally n - ary. cardinality ratios are used to specify how many tuples are interrelated as part of a binary relationship ( i. e., 1 - 1, 1 - n, n - 1, m - n ). multivalued attributes are allowed in er models. they are used to represent an attribute that contains a list of values. for example, a car ... | openstax_introduction_to_computer_science_-_web | [
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is more appropriate to merge both relations ( from the participating entities ) into one, or create a cross - reference ( i. e., relationship relation ) between the two relations. 4. mapping of binary 1 : n relationship types. create a relation for each participating entity. the primary key from the “ one ” side of the... | openstax_introduction_to_computer_science_-_web | [
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; option 8c : single | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 387 relation with one type attribute ; option 8d : single relation with multiple type attributes. 9. mapping of union types. for mapping a category whose defining superclass has different keys, it is customary to specify a new key attribute, called a surrogate key, when cre... | openstax_introduction_to_computer_science_-_web | [
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across an array of low - cost hard disks. figure 8. 9 this storage hierarchy includes primary and secondary storage. ( attribution : copyright rice university, openstax, under cc by 4. 0 license ) physical file organization and indexing file organization and indexing are used to minimize the number of block accesses fo... | openstax_introduction_to_computer_science_-_web | [
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: 1. parsing : checking the syntax of the query, user ’ s privileges, table, and attribute names 2. translation : translating from high - level language to machine language 3. optimizer : selecting the best plan to execute 4. execution : running the selected plan 5. evaluation : returning the query result the query opt... | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 389 employee number fname lname country 1 sam smith usa 2 adam bell uk 3 matt john usa 4 john zack usa 5 andy dave uk table 8. 9 employee table we are looking for “ andy ” using the following sql statement : select * from employee where fname ='andy'; looking for andy takes... | openstax_introduction_to_computer_science_-_web | [
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index, we need to decide which attribute we cluster. in general cases, the indexing is implemented using binary tree, b - tree, or b + tree. in practice, b + trees are more commonly used in database systems. binary tree is a tree in which every node has up to two children. b - tree generalizes the binary tree with more... | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 391 rdbms architectures a relational database management system ( rdbms ) architecture is categorized as a centralized system architecture and a tiered system architecture. in centralized system architecture, the dbms ’ s responsibilities are handled by one centralized enti... | openstax_introduction_to_computer_science_-_web | [
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returning the results. in many cases, the client and server interfaces are implemented to work over a computer network using network sockets. the main goal of a database api is to expose an interface through which other parties can utilize the services provided by the dbms. most dbms vendors provide a proprietary, dbms... | openstax_introduction_to_computer_science_-_web | [
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host language. they allow for efficient querying of objects ; such entities are frequently mapped to a relational database model using an object relational mapper ( orm ). it is not strictly necessary to utilize an orm to enable object persistence, though most apis tightly couple both concepts. sample rdbms application... | openstax_introduction_to_computer_science_-_web | [
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a schedule with interleaved read / write operations, guarantees acid properties, and can commit a transaction upon successful execution or rollback a transaction upon unsuccessful execution. delineating transactions within the transaction life cycle is called transaction management. various components are involved in t... | openstax_introduction_to_computer_science_-_web | [
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are performed across multiple database systems. distributed transaction management coordinates the resources between multiple databases. the transaction | openstax_introduction_to_computer_science_-_web | [
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8. 3 • relational database management systems 393 manager decides whether to commit or rollback a transaction using a two - phase commit ( 2pc ). the steps of 2pc are described in figure 8. 12. figure 8. 12 two - phase commit protocol illustrates the six steps needed for a distributed transaction. ( attribution : copyr... | openstax_introduction_to_computer_science_-_web | [
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be added. parallel databases focus on data distribution for performance and intraquery versus interquery parallelism. federated databases use nodes in a shared - nothing architecture, each running an independent dbms instance with horizontal data fragmentation. in distributed query processing, the optimizer should not ... | openstax_introduction_to_computer_science_-_web | [
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14 sql injection gives attackers access to confidential client data such as teacher data. ( attribution : copyright rice university, openstax, under cc by 4. 0 license ) to secure the database, there are many methods such as discretionary access control, which may grant or reject object access using a set of policies ;... | openstax_introduction_to_computer_science_-_web | [
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8. 4 nonrelational database management systems learning objectives by the end of this section, you will be able to : • discuss the various types of legacy database management systems • explain the functionality of non - first normal form ( nfnf ) database management systems • identify various characteristics of object ... | openstax_introduction_to_computer_science_-_web | [
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an example, ibm ims is a hierarchical database management software system for oltp. figure 8. 15 a hierarchical model shows a root parent connected to three child nodes. ( attribution : copyright rice university, openstax, under cc by 4. 0 license ) a hierarchical model has many limitations such as the complexity of na... | openstax_introduction_to_computer_science_-_web | [
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retrieve or save their state. in persistence independence, an object is independent of how a program manipulates it. there are many types of orthogonality. for example, all objects can be made persistent irrespective of their type or size, and they can achieve transitive persistence ( refers to persistence by reachabil... | openstax_introduction_to_computer_science_-_web | [
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one with mongodb within hours, which went to production in 90 days. extended relational databases extended relational databases ( erdbmss ) combine characteristics of rdbms and oodbms. the products of erdbmss provide a relational data model and query language that have been extended to include features of oodbmss. | openstax_introduction_to_computer_science_-_web | [
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8. 4 • nonrelational database management systems 397 limitations of the relational model the relational model has a flat structure, and expensive joins are needed to defragment the data before it can be successfully used, which increases the complexity of the objects due to normalization. specialization, categorization... | openstax_introduction_to_computer_science_-_web | [
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of nonrelational database management system for this application? xml databases extensible markup language ( xml ) is a markup language similar to html, but users define their tags ; predefined tags such as html are not used. the oldest schema language for xml is the document type definition ( dtd ). an xml schema is t... | openstax_introduction_to_computer_science_-_web | [
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s account and adding it to the recipient's account. if any of these steps fail, the entire transaction should be rolled back to ensure that the database remains consistent. atomicity ensures that the transaction either completes successfully and all the changes are committed, or it fails and none of the changes are com... | openstax_introduction_to_computer_science_-_web | [
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databases are schema - agnostic and provide the flexibility needed to store and manipulate large volumes of unstructured and semistructured data. users do not need to know what types of data are stored during setup, and the system can accommodate changes in data types and schema. designed to distribute data across diff... | openstax_introduction_to_computer_science_-_web | [
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8. 4 • nonrelational database management systems 399 key - value stores a key - value store is a simple database that uses an associative array such as redis, dynamodb, and cosmos db. it stores only key - value pairs, provides basic functionality for retrieving the value associated with a known key, and works best with... | openstax_introduction_to_computer_science_-_web | [
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this means that cassandra is optimized for high - speed reads and writes of individual rows, while hbase is optimized for scanning large tables of data. graph - based databases a graph - based database represents data as a network of related nodes or objects to facilitate data visualizations and graph analytics. the gr... | openstax_introduction_to_computer_science_-_web | [
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checks the availability of each node, which makes it easier to apply index between them but does not guarantee that every node is aware of every other node at all times. hashing is the process of transforming a key to another value to implement a hash table. consistent hashing avoids mapping each key to a new node in c... | openstax_introduction_to_computer_science_-_web | [
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8. 4 • nonrelational database management systems 401 figure 8. 18 this figure visualizes the tree - based dom api : ( a ) shows the input xml code, ( b ) highlights in - memory tree representation, and ( c ) demonstrates the corresponding dom tree. ( attribution : copyright rice university, openstax, under cc by 4. 0 l... | openstax_introduction_to_computer_science_-_web | [
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dataset grows or decreases as more or fewer users access the database, the system can quickly scale up or down its resources to handle the demand. blockchain dbmss the technology that records transitions securely is called blockchain. it has the world ’ s attention because of its use of cryptocurrencies such as bitcoin... | openstax_introduction_to_computer_science_-_web | [
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8. 5 data warehousing, data lakes, and business intelligence learning objectives by the end of this section, you will be able to : • outline the characteristics of data warehouses • explain the extraction, transformation, and loading ( etl ) process • discuss data marts • describe the technology behind virtual data war... | openstax_introduction_to_computer_science_-_web | [
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decisions happen frequently based on day - to - day operations and are structured based on a specific predefined role ( i. e., limited ). tactical - level decisions occur with greater frequency ( i. e., monthly ) and are semistructured based on the data requirement. the strategic level has the highest level of organiza... | openstax_introduction_to_computer_science_-_web | [
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8. 5 • data warehousing, data lakes, and business intelligence 403 figure 8. 19 a graphic shows an example of a star schema. ( attribution : copyright rice university, openstax, under cc by 4. 0 license ) the snowflake schema is a data model that normalizes the dimension table ( figure 8. 20 ). it has one fact table, a... | openstax_introduction_to_computer_science_-_web | [
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the data makes its way to the data warehouse. ( attribution : copyright rice university, openstax, under cc by 4. 0 license ) data marts a data mart is a scaled - down version of a data warehouse aimed at meeting the information needs of a homogeneous small group of end users such as a department or business unit. it p... | openstax_introduction_to_computer_science_-_web | [
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8. 5 • data warehousing, data lakes, and business intelligence 405 data stores ; data are only accessed ( “ pulled ” ) at query time. a virtual data warehouse can be built as a set of sql views directly on the underlying operational data sources as an extra layer on top of a collection of physical independent data mart... | openstax_introduction_to_computer_science_-_web | [
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new set of business questions or tackle old questions with new data. figure 8. 22 shows an example of a data lake process. figure 8. 22 a data lake stores structured, semistructured, and unstructured data. the store process stores the data as raw data lake then applies many processes such as cleansing and aggregation t... | openstax_introduction_to_computer_science_-_web | [
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to cost and the inability to adapt. seventy percent of development costs from etl include an effort to consolidate, prepare, standardize, and transform data for downstream analytics. costs involve initial capital investment for hardware, software licensing for databases, data integration, and analytics platforms. there... | openstax_introduction_to_computer_science_-_web | [
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8. 5 • data warehousing, data lakes, and business intelligence 407 link to learning data lakes are used to collect very large amounts of both relational and nonrelational data, such as a streaming service collecting data on users ’ watching habits, while data warehousing collects relational data, such as when a retaile... | openstax_introduction_to_computer_science_-_web | [
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and view data from multiple dimensions. it is used to analyze large volumes of data and is commonly used in bi applications. olap allows users to perform complex analysis of data by providing a multidimensional view of the data. it can aggregate data across multiple dimensions, such as time, location, product, and cust... | openstax_introduction_to_computer_science_-_web | [
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8. 6 data management for shallow and deep learning applications learning objectives by the end of this section, you will be able to : • define big data and explain its related functionality • discuss big data analytics and its impact on computer systems • identify and describe the tools that are used to perform shallow... | openstax_introduction_to_computer_science_-_web | [
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. the five vs of big data big data helps the decision - makers to improve their decisions, which in turn improves the quality of their products and services. big data has many characteristics. researchers defined the scope of big data as five vs ( figure 8. 24 ) : • volume : the amount of data ; also referred to as dat... | openstax_introduction_to_computer_science_-_web | [
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a data warehouse is data consolidation. the use of enterprise information integration ( eii ) to provide a unified view over data sources is data federation. the use of enterprise application integration ( eai ) corresponding to the synchronous or asynchronous propagation of updates in a source system to a target syste... | openstax_introduction_to_computer_science_-_web | [
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8. 6 • data management for shallow and deep learning applications 409 within the business process to improve performance. the main challenge of combining traditional data types with new data types is integrating the diverse data types in such a way that they can be processed and analyzed efficiently. data quality and m... | openstax_introduction_to_computer_science_-_web | [
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data governance. a well - articulated data governance program is a good starting point. approaches include centralized ( i. e., central department of data scientists handling all analytics requests ), decentralized ( i. e., all data scientists are directly assigned to business units ), and mixed ( i. e., centrally coor... | openstax_introduction_to_computer_science_-_web | [
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confidential and are not disclosed to unauthorized users ), auditing ( i. e., tracking all access and activity related to data ), and vulnerabilities ( i. e., identifying vulnerabilities in systems and data ). to better understand privacy, we should start with the raci ( responsible, accountable, consulted, and informe... | openstax_introduction_to_computer_science_-_web | [
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commodity hardware. concepts in practice private data and analytics all social media and search engine websites use data management for machine and deep learning applications. today there are major concerns related to the use of private data to perform analytics and support targeted sales or broadcast fake news to sele... | openstax_introduction_to_computer_science_-_web | [
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is to build a process that is easy to maintain and where models are iterated on, the performance is reproducible, and a model ’ s output can be easily understood and visualized for other stakeholders so that they may make informed business decisions. achieving those goals requires selecting the right tools as well as a... | openstax_introduction_to_computer_science_-_web | [
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8. 6 • data management for shallow and deep learning applications 411 what others in the industry are doing along with best practices. figure 8. 25 shows the three - stage process of the analytics process model, which we discuss next. figure 8. 25 the three - stages of the analytics process model are shown. ( attributi... | openstax_introduction_to_computer_science_-_web | [
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, decision trees ) is predictive analysis. evaluating predictive models splits up the dataset with specific performance measures. patterns of customer behavior ( e. g., association rules, sequence rules, 412 8 • data management access for free at openstax. org and clustering ) are considered descriptive analytics. glob... | openstax_introduction_to_computer_science_-_web | [
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return on investment ( roi ) determines the ratio of net profits divided by the investment of resources. think it through machine learning you are given a dataset that pertains to hospital patients affected with a particular condition and you are asked to create a predictive model that could be used to assess testing n... | openstax_introduction_to_computer_science_-_web | [
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8. 6 • data management for shallow and deep learning applications 413 step is distributing data across multiple computers ( map ) with each performing a computation on its slice of the data in parallel. the next step combines those results in a pair - wise manner ( reduce ). figure 8. 27 after the data input stage, map... | openstax_introduction_to_computer_science_-_web | [
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in a way that allows it to be easily accessed and used for analytics purposes. sql on hadoop because of the complexity of mapreduce in a database query, many industries create other solutions. in 2007, hadoop included the first version of hbase as a data storage platform. hbase offers a simplified structure and query l... | openstax_introduction_to_computer_science_-_web | [
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data in real time. azure stream analytics is a real - time analytics event - processing engine to analyze big data streaming from multiple sources. on - premises vs. cloud solutions another innovation that has completely transformed enterprise big data analytics capabilities is the rise of cloud services. before cloud ... | openstax_introduction_to_computer_science_-_web | [
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information in documents using retrieval models that specify matching functions and query representation is information retrieval. enterprises use a variety of retrieval models for intranet, web search, and analysis such as keyword queries that use a keyword to retrieve documents, boolean queries that use logical opera... | openstax_introduction_to_computer_science_-_web | [
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8. 6 • data management for shallow and deep learning applications 415 queries that check how close to each other within a record multiple entities are, wild card queries that support matching expressions, and natural language queries that try to formulate answers to a specific question from retrieved results. searching... | openstax_introduction_to_computer_science_-_web | [
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##tribution : copyright rice university, openstax, under cc by 4. 0 license ) sample ai applications amazon provides various ml services. they allow developers to integrate cloud ml into mobile and other applications. amazon lex allows users to incorporate voice input into applications ( extension of amazon ’ s echo pr... | openstax_introduction_to_computer_science_-_web | [
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##xs / wikimedia commons, cc0 ) cognitive analytics frameworks for deep machine learning in this section, we introduce examples of cognitive analytics frameworks for deep machine learning applications such as spark mllib, amazon machine learning platform and mxnet, google tensorflow, azure machine learning platform, an... | openstax_introduction_to_computer_science_-_web | [
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8. 6 • data management for shallow and deep learning applications 417 azure machine learning platform and microsoft cognitive toolkit the microsoft cognitive toolkit software is available for download in a variety of formats so that deep learning examples can be run on azure as clusters of docker containers ( i. e., mu... | openstax_introduction_to_computer_science_-_web | [
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##using solutions such as amazon redshift, which is a data warehouse cloud platform for amazon web services, and pivotal greenplum, which is a big data technology based on mpp architecture combined with an open - source database. | openstax_introduction_to_computer_science_-_web | [
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8. 7 informatics and data management learning objectives by the end of this section, you will be able to : • define informatics and discuss its applications in various industries • explain the role and life cycle of information systems as discussed earlier, the data analysis process produces reports that help the decis... | openstax_introduction_to_computer_science_-_web | [
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records relevant to an organization. these systems also help informatics professionals turn data and information into actionable knowledge from a user - centered perspective within the context of specific disciplines or industry such as health or sports. helping uncover critical information that can improve the user ex... | openstax_introduction_to_computer_science_-_web | [
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8. 7 • informatics and data management 419 chapter review key terms analytics process model provides a statistical analysis using a set of processes to solve system problems and find a new market opportunity archival backup storing the data in different servers / sites asynchronous call client sends a request without w... | openstax_introduction_to_computer_science_-_web | [
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uses the cloud to store, process, and manage data data completeness degree to which all data in a specific dataset are available with a minimum percentage of missing data data compliance process that ensures that data practices align with external legal requirements and industry standards data consistency keeping data ... | openstax_introduction_to_computer_science_-_web | [
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target system data quality ( dq ) measure of how well the data represents its purpose or fitness for use data quality dimension includes accuracy, completeness, consistency, and accessibility data query language ( dql ) language used to make various queries in a database data redundancy happens when the same piece of d... | openstax_introduction_to_computer_science_-_web | [
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security using a set of controls to secure data, guaranteeing a high level of confidentiality database transaction sequence of read / write operations considered to be an atomic unit database user person with the privileges to access, analyze, update, and maintain the data dbms interface main line of communication betw... | openstax_introduction_to_computer_science_-_web | [
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functional dependency ( fd ) constraint that specifies the relationship between two sets of attributes and provides a formal tool for the analysis of relational schemas garbage in, garbage out ( gigo ) quality of output is determined by the quality of the input graph - based database database that represents data as a ... | openstax_introduction_to_computer_science_-_web | [
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analysis, design, implementation, and validation and acceptance testing 422 8 • chapter review access for free at openstax. org mapreduce open - source software framework used to apply complex queries master data management ( mdm ) series of processes, policies, standards, and tools to help organizations define and pro... | openstax_introduction_to_computer_science_-_web | [
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graph, key - value stores, and column - oriented databases object persistence refers to when an object is not deleted until a need emerges to remove it from memory object - oriented dbms data model in which the data are organized into an oo data model as no impedance mismatch in combination with the oo host language on... | openstax_introduction_to_computer_science_-_web | [
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database query language for relational databases based on domain relational calculus redundant array of inexpensive disks ( raid ) stores information across an array of low - cost hard disks reinforcement machine learning method based on encouraging desired behaviors and removing undesired behaviors relation mathematic... | openstax_introduction_to_computer_science_-_web | [
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the service tablespace where tables are stored physically in the memory theta join allows merging two tables based on a theta condition thin client variant where only the presentation logic is handled by the client and applications and database commands are executed on the server ; it is common when application logic a... | openstax_introduction_to_computer_science_-_web | [
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extra layer on top of a collection of physical independent data marts volume amount of data ; data at rest weak entity type of entity that cannot be uniquely identified based on its attributes alone and must rely on a strong entity to provide the context necessary for identification xml dbms data model in which the dat... | openstax_introduction_to_computer_science_-_web | [
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8. 1 data management focus • to make a decision, data should be formatted and converted to information. knowledge comes after processing the information. • metadata are data about data and are stored in catalogs. the catalog provides an important source of information for end users. • data quality represents the measur... | openstax_introduction_to_computer_science_-_web | [
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8. 2 data management systems • to store, retrieve, edit, and maintain the related data in the database, we need a system that is a database management system ( dbms ). • a database can be defined as a collection of related data items within a specific business process or problem setting. • a dbms is the software packag... | openstax_introduction_to_computer_science_-_web | [
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8. 3 relational database management systems • the relational model of data is based on the mathematical concept of a relation. • relational database management systems ( rdbmss ) are one type of dbms that stores related data elements in a row - based table structure. • sql is a language used in programming and managing... | openstax_introduction_to_computer_science_-_web | [
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8. 4 nonrelational database management systems • a nonrelational database is a database that does not use traditional ways for storing data. • flat file databases and multifile relational databases are the two main legacy dbms. • a hierarchical model is a model in which data are stored in the form of records and organi... | openstax_introduction_to_computer_science_-_web | [
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8. 5 data warehousing, data lakes, and business intelligence • a data warehouse is a relational database that stores processed data that are optimized for gathering 426 8 • chapter review access for free at openstax. org business insights to support decision - making process. • in designing a data warehouse, many schem... | openstax_introduction_to_computer_science_-_web | [
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8. 6 data management for shallow and deep learning applications • data integration aims to provide a unified view and / or unified access over heterogeneous, and possibly distributed, data sources. • big data encompasses both structured and highly unstructured forms of data. • the scope of big data has five vs : volume... | openstax_introduction_to_computer_science_-_web | [
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8. 7 informatics and data management • informatics describes the study, design, and development of information technology for the good of people, organizations, and society. • information systems clearly support informatics and provide an organizational context for using database systems to help collect, organize, stor... | openstax_introduction_to_computer_science_-_web | [
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environment. 3. what are three examples of data quality parameters? a. size, accuracy, and variety of sources b. accuracy, age of data, and size c. accuracy, security, and variety of sources d. accessibility, accuracy, and security 4. define data governance. 5. what is metadata and what is involved in cataloging them? ... | openstax_introduction_to_computer_science_-_web | [
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cloud. d. a separation of logical layers and presentation layers of data 11. give a few examples of data models and explain how they differ from one another. 12. give examples of dbms users. 13. what type of systems is described where the presentation layer is only on the client device but the application and data laye... | openstax_introduction_to_computer_science_-_web | [
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b. data stored without organization to make retrieval easy c. a large data repository that stores raw data and can be set up without having to first define the 8 • chapter review 429 data structure and schema d. centralizes an enterprise ’ s data from its databases, supporting the flow of data from operational systems ... | openstax_introduction_to_computer_science_-_web | [
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relate to the various level of abstractions encountered when managing data. these levels are known ( going from top to bottom ) as data, information, knowledge, and wisdom. can you explain why we use a pyramid to represent the levels of abstraction? give a specific example of a pyramid starting with actual data. can yo... | openstax_introduction_to_computer_science_-_web | [
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than the third normal form. • the second normal form is more strict than the boyce - codd normal form. • the first normal form is more strict than the boyce - codd normal form. 6. give practical examples of applications where it would be best to use the following : key - value store, document store, column - oriented d... | openstax_introduction_to_computer_science_-_web | [
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a given project. 7. research some popular sql and nosql tools. create a list of tools that are available for each database type. download a version of an sql and nosql tool of your choice and create a table in each. 8. contrast operational, tactical, and strategic decision - making. illustrate with an example in 8 • ch... | openstax_introduction_to_computer_science_-_web | [
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be filled. which record organization technique would be preferred for this purpose? why would it be the best choice? 6. select a key - value store of your choice and implement a sample application using it. 7. discuss four approaches to deal with slowly changing dimensions in a data warehouse. can any of these approach... | openstax_introduction_to_computer_science_-_web | [
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give some precise examples and explain how the start - up would be able to scale this approach. 3. consider our start - up company that is 100 % committed to leveraging innovative technologies as a business growth facilitator. describe how it could use a “ universal ” approach to apply a rdbms to all possible data mana... | openstax_introduction_to_computer_science_-_web | [
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describe how it could put together a generic framework to support informatics applications in any domain. does such a solution exist already? either way, how would the start - up be able to scale this approach? labs 1. search online to learn what a virtual machine is. you are setting up a virtual machine ( vm ) on micr... | openstax_introduction_to_computer_science_-_web | [
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the dataset because it is intended for multiple purposes downstream, such as aws redshift for relational analytics, aws elasticsearch for text search, or an optimized distributed file system for low - cost active archive storage, which can be queried with an mpp sql engine. 6. investigate how to put together an end - t... | openstax_introduction_to_computer_science_-_web | [
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: modification of “ lexus lf - a ” by nan palmero / flickr, cc by 2. 0 ; credit right : modification of " m25, orbital, approaching bright - heads up display " by jay galvin / flickr, cc by 2. 0 ) chapter outline 9. 1 software engineering fundamentals 9. 2 software engineering process | openstax_introduction_to_computer_science_-_web | [
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9. 3 special topics introduction what is software engineering? why is software engineering important? how is software engineering done? well, software engineering impacts every industry and all aspects of life. one sector where software engineering has been revolutionary is the automobile industry. software that has be... | openstax_introduction_to_computer_science_-_web | [
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years ago had little to no software engineering in its operation. in today ’ s automobile industry, software engineers are creating a variety of solutions that are incorporated throughout a vehicle. this ranges from the software running on interactive screens on dashboards that feature music systems and navigational ai... | openstax_introduction_to_computer_science_-_web | [
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engineers to understand their role and to familiarize themselves with software engineering processes, the types of solutions and technologies that are available, and their applicability to a given project at a given time. consider a scenario in which a software engineer is working at a company called techworks. the eng... | openstax_introduction_to_computer_science_-_web | [
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9. 1 software engineering fundamentals learning objectives by the end of this section, you will be able to : • describe the intent of software engineering and how it relates to computer science • recognize various categories of software • identify the skills that are required for a software engineer this section introd... | openstax_introduction_to_computer_science_-_web | [
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, is covered in detail as part of this chapter. concepts in practice software and our daily lives software is everywhere, and most of us interact with a software system on a daily basis. yet the importance of software is expected to grow even greater in the coming decades. although most software revenue comes from a ge... | openstax_introduction_to_computer_science_-_web | [
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