Index
A
- activation function / Predicting with logistic regression
- Adaptive Join / Batch mode adaptive joins
- adaptive query processing
- about / Adaptive query processing in SQL Server 2017
- interleaved execution / Interleaved execution
- batch mode adaptive memory grant feedback / Batch mode adaptive memory grant feedback
- batch mode adaptive joins / Batch mode adaptive joins
- advanced graphing
- about / Advanced graphing
- with ggplot2 / Introducing ggplot2, Advanced graphs with ggplot2
- affinity grouping / Advanced analysis – undirected methods
- aligned index / Leveraging table partitioning
- AllegroGraph
- about / AllegroGraph
- reference / AllegroGraph
- Allen's interval algebra / Allen's interval algebra
- Allen's operators / Allen's interval algebra
- ALTER COLUMN command / Online ALTER COLUMN
- Always Encrypted (AE) / Always Encrypted
- Amazon Neptune
- about / Amazon Neptune
- reference / Amazon Neptune
- analysis of variance / Continuous and discrete variables
- Analysis Services models / SQL Server Data Tools
- analytical queries / Analytical queries in SQL Server
- anomaly detection / Principal Components and Exploratory Factor Analysis
- ANOVA / Continuous and discrete variables
- application time / Types of temporal tables
- application time period tables / Temporal features in SQL:2011
- arguments, STRING_ESCAPE function
- text / Using STRING_ESCAPE
- association rules / Advanced analysis – undirected methods
- associations
- about / Intermediate statistics – associations
- finding, between continuous variables / Finding associations between continuous variables
- asymmetric key encryption / Encrypting the data
- AT TIME ZONE function
- using / Using AT TIME ZONE
- authentication / SQL Server security basics
- authorization / SQL Server security basics
- automatic tuning
- offline recommendations mode / Automatic tuning in SQL Server 2017
- mode / Automatic tuning in SQL Server 2017
- regressed queries, in sys.dm_db_tuning_recommendations view / Regressed queries in the sys.dm_db_tuning_recommendations view
- about / Automatic tuning
- Availability Groups (AGs) / Limitations of SQL Server on Linux
- Azure Cosmos DB
- about / Azure Cosmos DB
- reference / Azure Cosmos DB
- Azure Machine Learning (Azure ML) / SQL Server R Machine Learning Services
B
- backup encryption / Leveraging SQL Server data encryption options
- balanced tree (B-tree) / Benefits of clustered indexes
- basket analysis / Advanced analysis – undirected methods
- batch mode adaptive joins
- about / Batch mode adaptive joins
- disabling / Disabling adaptive batch mode joins
- batch mode processing / Batch processing
- batch processing / Columnar storage and batch processing, Batch processing
- benefits, stored procedures
- data abstraction / Data abstraction—views, functions, and stored procedures
- security / Data abstraction—views, functions, and stored procedures
- performance / Data abstraction—views, functions, and stored procedures
- usage / Data abstraction—views, functions, and stored procedures
- binary large objects (BLOBs) / Performance considerations
- bitemporal tables / Types of temporal tables, Temporal features in SQL:2011
- bitmap filtered hash join / Joins and indexes
- buckets / Joins and indexes
- business intelligence (BI)
- about / Business intelligence
- R, using in SQL server / R in SQL server
- Bw-tree / Non-clustered index
C
- certificate / Encrypting the data
- checkpoint file pairs (CFPs) / Data durability concerns
- Chemical graph theory (CGT) / Graph theory in the real world
- chi-squared critical points / Exploring discrete variables
- chi-squared test of independence / Exploring discrete variables
- class / Python language basics
- classification / Advanced analysis – directed methods
- CLR
- integration / CLR integration
- clustered columnstore indexes (CCI)
- about / Development of columnar storage in SQL Server, Clustered columnstore indexes
- compression and query performance / Compression and query performance
- testing / Testing the clustered columnstore index
- archive compression, using / Using archive compression
- B-tree indexes, adding / Adding B-tree indexes and constraints
- constraints, adding / Adding B-tree indexes and constraints
- updating / Updating a clustered columnstore index
- rows, deleting / Deleting from a clustered columnstore index
- clustered index (CI)
- benefits / Benefits of clustered indexes
- about / Development of columnar storage in SQL Server
- clustering / Advanced analysis – undirected methods, Finding groups with clustering
- clustering algorithms
- partitioning methods / Finding groups with clustering
- hierarchical methods / Finding groups with clustering
- density-based methods / Finding groups with clustering
- model-based methods / Finding groups with clustering
- Code Access Security (CAS) / CLR integration
- CodePlex
- reference / Introducing data structures in R
- cold data / Operational analytics
- column-level encryption / Leveraging SQL Server data encryption options
- column aliases / Core Transact-SQL SELECT statement elements
- columnar storage
- about / Columnar storage and batch processing
- and compression / Columnar storage and compression
- rows, recreating / Recreating rows from columnar storage
- creation process / Columnar storage creation process
- developing / Development of columnar storage in SQL Server
- column encryption key (CEK) / Always Encrypted
- column master key (CMK) / Always Encrypted
- combination function / Predicting with logistic regression
- comma-separated values (CSV) / Introducing data structures in R
- common tables expressions (CTEs) / The mighty Transact-SQL SELECT
- Community Technology Preview (CTP) / Release cycles
- Comprehensive R Archive Network (CRAN)
- reference / Starting with R
- COMPRESS function
- using / Using COMPRESS
- CONCAT_WS function
- using / Using CONCAT_WS
- conditional DROP statement (DROP IF EXISTS) / The conditional DROP statement (DROP IF EXISTS)
- conditional inference trees / Advanced analysis – directed methods, Classifying and predicting with decision trees
- Consumer Electronics (CE) / What is JSON?
- container
- about / Containers
- creating / Creating our first container
- container service
- installing / Installing the container service
- data persistence, with Docker / Data persistence with Docker
- contingency tables / Exploring discrete variables
- continuous integration/deployment (CI/CD) / SQL Server Data Tools
- continuous variables / Continuous and discrete variables
- correlated subquery / Advanced SELECT techniques
- covariance / Finding associations between continuous variables
- CREATE OR ALTER
- using / Using CREATE OR ALTER
- cross-tabulated format / Exploring discrete variables
- cross join / Advanced SELECT techniques
- Cumulative Updates (CU) / Installing and updating SQL Server Tools
- current table / Updating data in temporal tables
- CURRENT_TRANSACTION_ID function
- using / Using CURRENT_TRANSACTION_ID
D
- data
- manipulating / Manipulating data
- about / Understanding data
- basic visualizations / Basic visualizations
- statistics / Introductory statistics
- working with / Working with data
- organizing, with pandas / Organizing data with pandas
- data-reduction technique / Principal Components and Exploratory Factor Analysis
- data-science project
- with Python / Data science with Python
- graphs, creating / Creating graphs
- advanced analytics, performing / Performing advanced analytics
- Python, using in SQL Server / Using Python in SQL Server
- reference / Using Python in SQL Server
- database administrator (DBA) / Triggers
- database encryption key (DEK) / Leveraging SQL Server data encryption options
- database management systems (DBMSs) / Types of temporal tables
- Database Master Key (DMK) / Encrypting the data
- Database Stretch Unit (DSU) / SQL Server Stretch Database pricing
- database time / Types of temporal tables
- data compression
- about / Data compression and query techniques
- efficient queries, writing / Writing efficient queries
- data compression implementations
- row compression / Data compression and query techniques
- page compression / Data compression and query techniques
- Data Control Language (DCL) / Defining principals and securables
- data definition language (DDL)
- about / DDL, DML, and programmable objects, Defining principals and securables
- statements / Data definition language statements
- enhancements / Enhanced DML and DDL statements
- data durability
- concerns / Data durability concerns
- data encryption / Encrypting the data
- data frame / Introducing data structures in R
- data management
- sorting / Getting sorted with data management
- data manipulation
- and querying / Querying and data manipulation
- performance comparisons / Performance comparisons
- natively compiled stored procedures / Natively compiled stored procedures
- concurrency / Looking behind the curtain of concurrency
- data manipulation language (DML)
- about / DDL, DML, and programmable objects, Object and statement permissions
- statements / Data modification language statements
- enhancements / Enhanced DML and DDL statements
- data mining / Introducing R
- Data Protection Application Programming Interface (DPAPI) / Encrypting the data
- data structures
- in R / Introducing data structures in R
- data warehouses / SQL Server 2016 and 2017 temporal tables and data warehouses
- DATEDIFF_BIG function
- using / Using DATEDIFF_BIG
- decision trees
- about / Advanced analysis – directed methods, Classifying and predicting with decision trees
- classifying / Classifying and predicting with decision trees
- predicting / Classifying and predicting with decision trees
- declarative Row-Level Security / Row-Level Security
- DECOMPRESS function
- using / Using DECOMPRESS
- degrees of freedom / Introductory statistics
- delimited identifiers / Core Transact-SQL SELECT statement elements
- dendrogram / Finding groups with clustering
- dependent variable / Intermediate statistics – associations
- derived table / Advanced SELECT techniques
- descriptive statistics / CLR integration
- deterministic encryption / Always Encrypted
- deviation / Introductory statistics
- dictionary / Python language basics
- dictionary compression / Data compression and query techniques
- dimensionality reduction / Advanced analysis – undirected methods
- dimensions / SQL Server 2016 and 2017 temporal tables and data warehouses, Analytical queries in SQL Server
- directed approach / Advanced analysis – undirected methods
- directed methods / Advanced analysis – directed methods
- discrete variables
- exploring / Exploring discrete variables
- about / Continuous and discrete variables
- Distributed Transaction Coordinator (DTC) / Limitations of SQL Server on Linux
- dockerfile / Data persistence with Docker
- DSE Graph
- reference / DSE Graph
- about / DSE Graph
- dynamic data masking (DDM)
- about / Dynamic data masking, Exploring dynamic data masking
- exploring / Exploring dynamic data masking
- reference link / Exploring dynamic data masking
- masked columns, defining / Defining masked columns
- limitations / Dynamic data masking limitations
- Dynamic Management Objects (DMOs) / Looking behind the curtain of concurrency
- Dynamic Management View (DMV) / Using CURRENT_TRANSACTION_ID, Adding B-tree indexes and constraints
E
- edge tables / Edge tables
- eigenvalue / Principal Components and Exploratory Factor Analysis
- eigenvectors / Principal Components and Exploratory Factor Analysis
- encryptor / Leveraging SQL Server data encryption options
- Engine features
- about / Engine features
- Query Store / Query Store
- live query statistics / Live query statistics
- stretch database / Stretch Database
- database scoped configuration / Database scoped configuration
- temporal tables / Temporal Tables
- columnstore indexes / Columnstore indexes
- containers, on Linux / Containers and SQL Server on Linux
- SQL Server, on Linux / Containers and SQL Server on Linux
- enhancements, In-Memory OLTP engine
- indexing / Down the index rabbit-hole
- large object support / Large object support
- on-row data storage, versus off-row data storage / Storage differences of on-row and off-row data
- cross-feature support / Cross-feature support
- security / Security
- programmability / Programmability
- high availability / High availability
- tools and wizards / Tools and wizards
- equijoin / Joins and indexes
- error handling / Transactions and error handling, Error handling
- estimation / Advanced analysis – directed methods
- Euclidean (flat) coordinate system / Spatial data
- Exploratory Factor Analysis (EFA) / Principal Components and Exploratory Factor Analysis
- extended events / Extended events
- Extended Events (XE) / Altering temporal tables
- Extensible Key Management (EKM) / Encrypting the data
- Extract-Transform-Load (ETL) / Leveraging table partitioning
- eXtreme Transaction Processing (XTP) / Dynamic management objects
F
- faceted graphs / Advanced graphs with ggplot2
- fact table / Analytical queries in SQL Server
- Flashback Data Archive (FDA) / Temporal features in SQL:2011
- FlockDB
- reference / FlockDB
- about / FlockDB
- forecasting / Advanced analysis – directed methods
- FOR JSON PATH
- about / FOR JSON PATH
- additional options / FOR JSON additional options
- root node, adding / Add a root node to JSON output
- NULL values, including in JSON output / Include NULL values in the JSON output
- JSON output, formatting as single object / Formatting a JSON output as a single object
- full-text indexes / Full-text indexes
- fully temporal data / What is temporal data?
- functions / Data abstraction—views, functions, and stored procedures
G
- Garbage Collector (GC) / Non-clustered index
- Global Positioning System (GPS) / Spatial data
- graph
- about / What is a graph?
- theory / Graph theory in the real world
- graph database
- about / Introduction to graph databases, What is a graph database?
- using / When should you use graph databases?
- commercial and open source graph databases / Graph databases market
- graph databases, in market
- Neo4j / Neo4j
- Azure Cosmos DB / Azure Cosmos DB
- OrientDB / OrientDB
- FlockDB / FlockDB
- DSE Graph / DSE Graph
- Amazon Neptune / Amazon Neptune
- AllegroGraph / AllegroGraph
- graph features
- node tables / Node tables
- edge tables / Edge tables
- MATCH clause / The MATCH clause
- SQL Graph system functions / SQL Graph system functions
- groups
- finding, with clustering / Finding groups with clustering
H
- hardware security module (HSM) / Always Encrypted
- hash algorithm / Encrypting the data
- hash bucket / Hash indexes
- HASHBYTES function
- using / Using HASHBYTES
- hash function / Joins and indexes
- Hash Match operator / Joins and indexes
- heap / Benefits of clustered indexes
- history retention policy
- about / History retention policy in SQL Server 2017
- configuration, at database level / Configuring the retention policy at the database level
- configuring, at table level / Configuring the retention policy at the table level
- custom history data retention / Custom history data retention
- history table implementation / History table implementation
- history table / History table overhead
- history table / Updating data in temporal tables
- hot data / Operational analytics
- human time / Types of temporal tables
I
- In-Memory objects
- managing / Management of In-Memory objects
- dynamic management objects / Dynamic management objects
- In-Memory OLTP
- reference / Querying and data manipulation
- In-Memory OLTP, limitations
- URL / Types of data
- indexes / What's new with indexes?
- unconstrained integrity / Unconstrained integrity
- operator equality, checking / Not all operators are created equal
- size / Size is everything!
- In-Memory OLTP architecture
- about / In-Memory OLTP architecture
- index storage / Row and index storage
- rows structure / Row structure
- row header / Row header
- row payload / Row payload
- index structure / Index structure
- non-clustered index / Non-clustered index
- In-Memory OLTP engine
- feature, enhancements / Feature improvements
- collations / Collations
- computed columns, for performance / Computed columns for greater performance
- data, types / Types of data
- enhancements / Improvements in the In-Memory OLTP engine
- independent variable / Intermediate statistics – associations
- index
- non-clustered index / Non-clustered index
- hash indexes / Hash indexes
- indexed views
- using / Using indexed views
- Information and Communication Technology (ICT) / What is JSON?
- inline table-valued function / Data abstraction—views, functions, and stored procedures
- input unit / Predicting with logistic regression
- Integration Services packages / SQL Server Data Tools
- inter-quartile range (IQR) / Introductory statistics
- intercept / Getting deeper into linear regression
- interleaved execution / Interleaved execution
- intermediate statistics
- about / Intermediate statistics – associations
- discrete variables, exploring / Exploring discrete variables
- associations, finding between continuous variables / Finding associations between continuous variables
- discrete variables / Continuous and discrete variables
- continuous variables / Continuous and discrete variables
- linear regression / Getting deeper into linear regression
- Internet Movie Database (IMDb)
- reference / Advanced MATCH queries
- Internet Protocol Security (IPSec) / Encrypting the data
- iterators / Joins and indexes
J
- JavaScript Object Notation (JSON)
- need for / Why JSON?
- about / What is JSON?, JSON in SQL Server prior to SQL Server 2016
- features / Why is it popular?
- versus XML / JSON versus XML
- primitive value / JSON objects
- complex value / JSON objects
- JSON.SQL
- about / JSON.SQL
- reference / JSON.SQL
- JSON4SQL
- reference / JSON4SQL
- about / JSON4SQL
- JSON array / JSON array
- JSON data
- converting, in tabular format / Converting JSON data in a tabular format
- validating / Validating JSON data
- modifying / Modifying JSON data
- JSON property, adding / Adding a new JSON property
- JSON property value, updating / Updating the value for a JSON property
- JSON property, removing / Removing a JSON property
- multiple changes / Multiple changes
- JSON functions
- using / Using JSON functions
- JSON object / JSON object
- JSON text
- values, extracting / Extracting values from a JSON text
K
- K-means algorithm / Finding groups with clustering
- K-means clustering algorithm / Creating scalable solutions
- K-medoids / Finding groups with clustering
- kurtosis / Introductory statistics
L
- large data object types (LOBs) / Types of data
- Launchpad / Discovering SQL Server R Machine Learning Services
- limitations, Stretch Database (Stretch DB)
- about / Limitations that prevent you from enabling the Stretch DB features for a table
- table limitations / Table limitations
- column limitations / Column limitations
- linear function / Getting deeper into linear regression
- linear regression / Intermediate statistics – associations, Getting deeper into linear regression
- Linux
- SQL Server, working / How SQL Server works on Linux
- lists / Introducing data structures in R
- logistic function / Predicting with logistic regression
- logistic regression
- about / Predicting with logistic regression
- predicting / Predicting with logistic regression
- Logistic Regression algorithm / Deploying R models
- lower quartile / Introductory statistics
- LZ77 compression / Data compression and query techniques
M
- machine learning / Introducing R
- masked columns
- defining / Defining masked columns
- MATCH clause
- about / The MATCH clause
- MATCH queries / Basic MATCH queries
- advanced MATCH queries / Advanced MATCH queries
- limitations / Limitations of the MATCH clause
- matrix / Introducing data structures in R
- MAX_GRANT_PERCENT
- using / Using MAX_GRANT_PERCENT
- mean / Introductory statistics
- median / Introductory statistics
- memory-optimized tables
- startup / Database startup and recovery
- recovery / Database startup and recovery
- creating / Ch-Ch-Changes
- memory-optimized tables and indexes
- creating / Creating memory-optimized tables and indexes
- foundation, laying / Laying the foundation
- table, creating / Creating a table
- message digest / Encrypting the data
- Microsoft R Application Network (MRAN)
- reference / Starting with R
- Microsoft R Server / Discovering SQL Server R Machine Learning Services
- MIN_GRANT_PERCENT
- using / Using MIN_GRANT_PERCENT
- multi-statement table-valued functions / Data abstraction—views, functions, and stored procedures
- Multi-Version Concurrency Control (MVCC) / Looking behind the curtain of concurrency
- multiple linear regression / Getting deeper into linear regression
N
- Neo4j
- about / Neo4j
- reference / Neo4j
- Network Address Translation (NAT) / Creating our first container
- node table / Node tables
- non-equijoin / Joins and indexes
- nonclustered columnstore indexes (NCCI)
- about / Nonclustered columnstore indexes
- compression and query performance / Compression and query performance
- testing / Testing the nonclustered columnstore index
- operational analytics / Operational analytics
- nonclustered index (NCI)
- maximum key size / Maximum key size for nonclustered indexes
- in analytical scenarios / Nonclustered indexes in analytical scenarios
- about / Clustered columnstore indexes
- NoSQL-based database solutions
- key-value store / Introduction to graph databases
- document store / Introduction to graph databases
- wide-column store / Introduction to graph databases
- graph databases / Introduction to graph databases
- NO_PERFORMANCE_SPOOL
- using / Using NO_PERFORMANCE_SPOOL
- null hypothesis / Exploring discrete variables
- NumPy data structures and methods
- using / Using the NumPy data structures and methods
O
- object members / JSON object
- object permissions / Object and statement permissions
- objects / Python language basics
- one-way ANOVA / Continuous and discrete variables
- OPENJSON, with explicit schema
- about / OPENJSON with an explicit schema
- JSON data, importing from file / Import the JSON data from a file
- OPENJSON function
- with defalut schema / OPENJSON with the default schema
- with explicit schema / OPENJSON with an explicit schema
- OPENJSON function, with default schema
- data, processing from comma-separated list of values / Processing data from a comma-separated list of values
- two table rows, difference / Returning the difference between two table rows
- operational analytics / Nonclustered columnstore indexes
- operators / Joins and indexes
- OrientDB
- about / OrientDB
- reference / OrientDB
- orthogonal / Principal Components and Exploratory Factor Analysis
- outer join / Core Transact-SQL SELECT statement elements
- output unit / Predicting with logistic regression
- Overall Resource Consumption report / Overall Resource Consumption report
- overfitting / Classifying and predicting with decision trees
P
- Page ID (PID) / Non-clustered index
- PageRank / Limitations of the MATCH clause
- pandas
- used, for data organization / Organizing data with pandas
- partial scans / Benefits of clustered indexes
- partition elimination / Leveraging table partitioning
- partition function / Leveraging table partitioning
- partition scheme / Leveraging table partitioning
- partition switching / Leveraging table partitioning
- PerfMon counters
- about / PerfMon counters
- In-Memory OLTP migration / Assistance in migrating to In-Memory OLTP
- performance considerations
- about / Performance considerations
- indexes on computed columns / Indexes on computed columns
- full-text indexes / Full-text indexes
- polymorphism / Limitations of the MATCH clause
- polynomial regression model / Getting deeper into linear regression
- predicate-based Row-Level Security
- about / Predicate-based Row-Level Security
- filter predicates / Predicate-based Row-Level Security
- block predicates / Predicate-based Row-Level Security
- primary key / Data definition language statements
- primary XML index / XML support in SQL Server
- primitive JSON data types
- numbers / Primitive JSON data types
- string / Primitive JSON data types
- true/false / Primitive JSON data types
- null / Primitive JSON data types
- Principal Component Analysis (PCA) / Principal Components and Exploratory Factor Analysis
- principal components (PC) / Principal Components and Exploratory Factor Analysis
- principals
- about / Defining principals and securables
- defining / Defining principals and securables
- private key / Encrypting the data
- probe phase / Joins and indexes
- programmable objects
- about / DDL, DML, and programmable objects
- used, to maintain security / Using programmable objects to maintain security
- programming
- about / Programming
- Transact SQL, enhancements / Transact-SQL enhancements
- JSON / JSON
- In-Memory OLTP / In-Memory OLTP
- SQL server tools / SQL Server Tools
- property graph model / What is a graph?
- public key / Encrypting the data
- Python
- starting with / Starting with Python
- machine learning services, installing / Installing machine learning services and client tools
- capabilities / A quick demo of Python's capabilities
- basics / Python language basics
- data-science project / Data science with Python
Q
- Queries With Forced Plans report / Queries With Forced Plans
- Queries With High Variation report / Queries With High Variation
- Query Editor / Always Encrypted
- query hints
- about / New query hints
- NO_PERFORMANCE_SPOOL, using / Using NO_PERFORMANCE_SPOOL
- MIN_GRANT_PERCENT, using / Using MIN_GRANT_PERCENT
- querying / Querying and data manipulation
- Query Store
- need for / Why Query Store?
- about / What is Query Store?
- architecture / Query Store architecture
- Query and Plan Store / Query Store architecture
- Runtime Statistics store / Query Store architecture
- Wait Stats Store / Query Store architecture
- reference / Query Store architecture
- configuring / Enabling and configuring Query Store, Configuring Query Store
- enabling / Enabling and configuring Query Store
- enabling, with SSMS / Enabling Query Store with SSMS
- enabling, with Transact-SQL / Enabling Query Store with Transact-SQL
- default configuration / Query Store default configuration
- recommended configuration / Query Store recommended configuration
- disabling / Disabling and cleaning Query Store
- cleaning / Disabling and cleaning Query Store
- using / Query Store in action
- info, capturing / Capturing the Query info
- plan info, capturing / Capturing plan info
- runtime statistics, collecting / Collecting runtime statistics
- and migration / Query Store and migration
- regressed queries, identifying / Query Store – identifying regressed queries
- regressed queries, fixing / Query Store – fixing regressed queries
- reports, in SQL Server Management Studio / Query Store reports in SQL Server Management Studio
- used, for capturing waits / Capturing waits by Query Store in SQL Server 2017
- use cases / Query Store use cases
- Query Store, parameters
- Operation Mode / Configuring Query Store
- Max Size (MB) / Configuring Query Store
- Statistics Collection Interval / Configuring Query Store
- Data Flush Interval (Minutes) / Configuring Query Store
- Query Store Capture Mode / Configuring Query Store
- Stale Query Threshold (Days) / Configuring Query Store
- Size Based Cleanup Mode / Configuring Query Store
- Query Store report
- regressed queries / Regressed queries
- Query Store reports
- in SQL Server Management Studio / Query Store reports in SQL Server Management Studio
- regressed queries report / Regressed queries
- Top resource consuming queries report / Top resource – consuming queries
- Overall Resource Consumption report / Overall Resource Consumption report
- Queries With Forced Plans report / Queries With Forced Plans
- Queries With High Variation report / Queries With High Variation
R
- R
- about / Introducing R
- using / Starting with R
- starting with / Starting with R
- basics / R language basics
- language basics / R language basics
- data structures / Introducing data structures in R
- randomized encryption / Always Encrypted
- range / Introductory statistics
- ranking functions / Advanced SELECT techniques
- R Console / RStudio IDE
- real-time scoring
- supported algorithms, reference / Deploying R models
- recursive partitioning / Classifying and predicting with decision trees
- regressed queries report / Regressed queries
- relational database management system (RDBMS) / Managing schemas, Columnar storage and batch processing
- relational databases / SQL Server Data Tools
- relational duplicates / Duplicates in an edge table
- relational model / Beyond relational
- Release To Market (RTM) / Release cycles
- Reporting Services reports / SQL Server Data Tools
- resumable online index rebuild operation / Resumable online index rebuild
- R Interactive / R Tools for Visual Studio 2015
- R Machine Learning Services (In-Database) / Discovering SQL Server R Machine Learning Services
- round-earth coordinate system / Spatial data
- Row-Level Security (RLS)
- about / Row-Level Security, Row-Level Security
- dynamic data masking / Dynamic data masking
- Always Encrypted / Always Encrypted
- row-rearranging algorithm / Columnar storage and compression
- row header
- Begin Ts section / Row header
- end TS section / Row header
- StmtId section / Row header
- IdxLinkCount section / Row header
- row reconstruction table / Recreating rows from columnar storage
- RStudio
- reference / RStudio IDE, Starting with R
- RStudio IDE / Tools for developing R and Python code, RStudio IDE
- R Tools for Visual Studio (RTVS) / Tools for developing R and Python code
- run-length encoding (RLE) / Columnar storage and compression
S
- scalable packages
- RevoScaleR / Discovering SQL Server R Machine Learning Services
- RevoPemaR / Discovering SQL Server R Machine Learning Services
- MicrosoftML / Discovering SQL Server R Machine Learning Services
- scalar functions / Data abstraction—views, functions, and stored procedures
- schemas
- managing / Managing schemas
- about / Managing schemas
- secret key encryption / Encrypting the data
- securables
- about / Data abstraction—views, functions, and stored procedures
- defining / Defining principals and securables
- Secure Sockets Layer (SSL) / Encrypting the data
- security
- about / Security
- Row-Level Security / Row-Level Security
- Engine features / Engine features
- programming / Programming
- business intelligence / Business intelligence
- release cycles / Release cycles
- self-contained subquery / Advanced SELECT techniques
- semi temporal data / What is temporal data?
- sequences / R language basics
- Service Master Key (SMK) / Encrypting the data
- Service Packs (SP) / Installing and updating SQL Server Tools
- SESSION_CONTEXT function
- using / Using SESSION_CONTEXT
- shortest path functionality / Limitations of the MATCH clause
- sigmoid / Predicting with logistic regression
- similarity / Finding groups with clustering
- single response variable / Intermediate statistics – associations
- skewness / Introductory statistics
- slope / Getting deeper into linear regression
- slowly changing dimensions (SCD) / SQL Server 2016 and 2017 temporal tables and data warehouses
- spatial data / Spatial data
- spatial reference identifier (SRID) / Spatial data
- SQL Graph limitations
- about / SQL Graph limitations
- general limitations / General limitations
- validation issues, in edge tables / Validation issues in edge tables
- non-existing node, referencing / Referencing a non-existing node
- duplicates, in edge table / Duplicates in an edge table
- parent records with children, deleting / Deleting parent records with children
- of MATCH clause / Limitations of the MATCH clause
- SQL Graph system functions
- about / SQL Graph system functions
- OBJECT_ID_FROM_NODE_ID function / The OBJECT_ID_FROM_NODE_ID function
- GRAPH_ID_FROM_NODE_ID function / The GRAPH_ID_FROM_NODE_ID function
- NODE_ID_FROM_PARTS function / The NODE_ID_FROM_PARTS function
- OBJECT_ID_FROM_EDGE_ID function / The OBJECT_ID_FROM_EDGE_ID function
- GRAPH_ID_FROM_EDGE_ID function / The GRAPH_ID_FROM_EDGE_ID function
- EDGE_ID_FROM_PARTS function / The EDGE_ID_FROM_PARTS function
- SQL Platform Abstraction Layer (SQLPAL) / How SQL Server works on Linux
- SQL Server
- XML support / XML support in SQL Server
- analytical queries / Analytical queries in SQL Server
- working, on Linux / SQL Server on Linux
- SQL Server, on Linux
- about / SQL Server on Linux
- limitations / Limitations of SQL Server on Linux
- installing / Installing SQL Server on Linux
- SQL Server 2016
- enhanced functions and expressions / New and enhanced functions and expressions
- SQL Server 2017
- adaptive query processing / Adaptive query processing in SQL Server 2017
- JSON storage / JSON storage in SQL Server 2017
- system-versioned temporal tables / System-versioned temporal tables in SQL Server 2017
- shortcomings / What is missing in SQL Server 2017?
- graph fetaures / Graph features in SQL Server 2017
- SQL Server Analysis Services (SSAS) / SQL Server R Machine Learning Services
- SQL Server data, retrieving in JSON format
- about / Retrieving SQL Server data in JSON format
- FOR JSON AUTO, using / FOR JSON AUTO
- FOR JSON PATH, using / FOR JSON PATH
- data types, converting / Converting data types
- escaping characters / Escaping characters
- SQL Server data encryption options
- leveraging / Leveraging SQL Server data encryption options
- SQL Server Data Tools (SSDT)
- about / SQL Server Tools, SQL Server Data Tools
- reference, for blog / SQL Server Data Tools
- SQL Server Installation Center / Installing and updating SQL Server Tools
- SQL Server Management Studio (SSMS) / SQL Server Tools, FOR JSON AUTO, Creating temporal tables, Enabling and configuring Query Store, Introducing R, Node tables
- SQL Server Operating System (SOS) / How SQL Server works on Linux
- SQL Server Reporting Services (SSRS) / SQL Server R Machine Learning Services
- SQL Server R Machine Learning Services
- about / SQL Server R Machine Learning Services
- discovering / Discovering SQL Server R Machine Learning Services
- scalable solutions, creating / Creating scalable solutions
- scalable solutions, deploying / Deploying R models
- R models, deploying / Deploying R models
- SQL Server security basics
- about / SQL Server security basics
- principals, defining / Defining principals and securables
- securables, defining / Defining principals and securables
- schemas, managing / Managing schemas
- object permissions / Object and statement permissions
- statement permissions / Object and statement permissions
- SQL Server table
- column altering, actions / Online ALTER COLUMN
- SQL Server Tools
- installing / Installing and updating SQL Server Tools
- updating / Installing and updating SQL Server Tools
- SSMS features and enhancements
- about / New SSMS features and enhancements
- Autosave open tabs / Autosave open tabs
- searchable options / Searchable options
- enhanced scroll bar / Enhanced scroll bar
- execution plan comparison / Execution plan comparison
- Live Query Statistics (LQS) / Live query statistics
- flat file wizard, importing / Importing flat file Wizard
- Vulnerability Assessment (VA) / Vulnerability assessment
- standard deviation / Introductory statistics
- standard deviation for the population / Introductory statistics
- statement permissions / Object and statement permissions
- statistics
- about / Introducing R
- mean / Introductory statistics
- median / Introductory statistics
- range / Introductory statistics
- deviation / Introductory statistics
- stored procedures / Data abstraction—views, functions, and stored procedures
- Stretch Database (Stretch DB)
- architecture / Stretch DB architecture
- local data / Stretch DB architecture
- staging (eligible data) / Stretch DB architecture
- remote data / Stretch DB architecture
- audiences / Is this for you?
- Data Migration Assistant, using / Using Data Migration Assistant
- limitations / Limitations of using Stretch Database, Limitations that prevent you from enabling the Stretch DB features for a table
- Stretch-enabled tables, limitations / Limitations for Stretch-enabled tables
- use cases / Use cases for Stretch Database
- enabling / Enabling Stretch Database
- enabling, at database level / Enabling Stretch Database at the database level
- enabling, by wizard usage / Enabling Stretch Database by using wizard
- enabling, by Transact-SQL / Enabling Stretch Database by using Transact-SQL
- enabling, for table / Enabling Stretch Database for a table
- enabling, for table by using wizard / Enabling Stretch DB for a table by using wizard
- enabling, for table with Transact-SQL / Enabling Stretch Database for a table by using Transact-SQL
- filter predicate, with sliding window / Filter predicate with sliding window
- querying / Querying stretch databases
- remote data, querying / Querying and updating remote data
- remote data, updating / Querying and updating remote data
- pricing / SQL Server Stretch Database pricing
- pricing, reference / SQL Server Stretch Database pricing
- STRING_AGG function
- using / Using STRING_AGG
- NULLs, handling / Handling NULLs in the STRING_AGG function
- WITHIN GROUP clause / The WITHIN GROUP clause
- STRING_ESCAPE function
- using / Using STRING_ESCAPE
- STRING_SPLIT function
- using / Using STRING_SPLIT
- supervised approach / Advanced analysis – undirected methods
- symmetric key encryption / Encrypting the data
- system-versioned tables / Temporal features in SQL:2011
- system time / Types of temporal tables
T
- table-valued parameters (TVP) / Using STRING_SPLIT
- table partitioning
- leveraging / Leveraging table partitioning
- temporal constraints / Temporal constraints
- temporal data
- about / What is temporal data?
- SQL Server before 2016 / Temporal data in SQL Server before 2016
- querying / Querying temporal data in SQL Server 2017
- retrieving, at specific point in time / Retrieving temporal data at a specific point in time
- retrieving, in specific period / Retrieving temporal data from a specific period
- retrieving / Retrieving all temporal data
- temporal feature
- in SQL 2011 / Temporal features in SQL:2011
- temporal queries
- optimizing / Optimizing temporal queries
- temporal tables
- types / Types of temporal tables
- working / How temporal tables work in SQL Server 2017
- creating / Creating temporal tables
- period columns as hidden attributes / Period columns as hidden attributes
- non-temporal tables, converting to / Converting non-temporal tables to temporal tables
- existing temporal solution, migrating to system-versioned tables / Migrating an existing temporal solution to system-versioned tables
- altering / Altering temporal tables
- dropping / Dropping temporal tables
- data manipulation / Data manipulation in temporal tables
- data, inserting / Inserting data in temporal tables
- data, updating / Updating data in temporal tables
- data, deleting / Deleting data in temporal tables
- performance and storage considerations / Performance and storage considerations with temporal tables
- with memory-optimized tables / Temporal tables with memory-optimized tables
- about / SQL Server 2016 and 2017 temporal tables and data warehouses
- test set / Advanced analysis – directed methods
- timestamped predicate / What is temporal data?
- tools, for developing Python cod
- RStudio IDE / RStudio IDE
- tools, for developing Python code / Tools for developing R and Python code
- tools, for developing R
- about / Tools for developing R and Python code
- RStudio IDE / RStudio IDE
- R Tools for Visual Studio 2015 / R Tools for Visual Studio 2015
- Top resource consuming queries report / Top resource – consuming queries
- training set / Advanced analysis – directed methods
- Transact-SQL
- used, for enabling QueryStore / Enabling Query Store with Transact-SQL
- Transact-SQL-based solution / Transact-SQL-based solution
- Transact-SQL SELECT
- core statement elements / Conventions used, Core Transact-SQL SELECT statement elements
- about / The mighty Transact-SQL SELECT
- advanced SELECT techniques / Advanced SELECT techniques
- transactions
- about / Transactions and error handling
- using / Using transactions
- transaction time / Types of temporal tables
- transfer function / Predicting with logistic regression
- transitive closure / Limitations of the MATCH clause
- TRANSLATE function
- using / Using TRANSLATE
- Transparent Data Encryption (TDE) / Leveraging SQL Server data encryption options, Security
- Transport Layer Security (TLS) / Encrypting the data
- trellis chart / Advanced graphs with ggplot2
- triggers / Triggers
- TRIM function
- using / Using TRIM
- TRUNCATE TABLE statement
- using / Using TRUNCATE TABLE
U
- undirected approach / Advanced analysis – undirected methods
- undirected methods / Advanced analysis – undirected methods
- unicode compression / Data compression and query techniques
- uniquifier / Benefits of clustered indexes
- unsupervised approach / Advanced analysis – undirected methods
- upper quartile / Introductory statistics
- use cases, Query Store
- about / Query Store use cases
- SQL Server version upgrades / SQL Server version upgrades and patching
- patching / SQL Server version upgrades and patching
- application and service releases / Application and service releases, patching, failovers, and cumulative updates
- failovers / Application and service releases, patching, failovers, and cumulative updates
- cumulative updates / Application and service releases, patching, failovers, and cumulative updates
- ad hoc queries, identifying / Identifying ad hoc queries
- unfinished queries, identifying / Identifying unfinished queries
- use cases, Stretch Database (Stretch DB)
- historical data, archiving / Archiving of historical data
- logging tables, archiving / Archiving of logging tables
- Azure SQL database, testing / Testing Azure SQL database
- user-defined aggregate (UDA) / CLR integration
- user-defined data types (UDT) / Converting data types
- user-defined functions (UDF) / Using STRING_SPLIT
V
- values, extracting from JSON text
- JSON_VALUE / JSON_VALUE
- JSON_QUERY / JSON_QUERY
- variance / Introductory statistics
- views / Data abstraction—views, functions, and stored procedures
- Virtual Network Interface Card (vNIC) / Creating our first container
- Visual Studio
- reference / Setting up Visual Studio 2017 for data science applications
- Visual Studio 2015
- R Tools / R Tools for Visual Studio 2015
- Visual Studio 2017
- setting up, for data science applications / Setting up Visual Studio 2017 for data science applications
W
- waits
- capturing, with Query Store / Capturing waits by Query Store in SQL Server 2017
- information, storing in sys.query_store_wait_stats / Catalog view sys.query_store_wait_stats
- warm data / Operational analytics
- weighted graph / What is a graph?
- window functions / Advanced SELECT techniques
X
- XML data / XML support in SQL Server
- XML XPath / XML support in SQL Server
- XPath / XML support in SQL Server
- XQuery / XML support in SQL Server
- XSD schema / XML support in SQL Server