SAP HANA PREDICTIVE ANALYTICS REPORT

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ANALYSIS

What You Need to Know

  • Breakouts in the SAP HANA predictive analytics are Predictive analytics, CAP theorem, NoSQL. Seriously consider these technologies to gain a strategic advantage.
  • The technologies who are at the peak of their interest are MariaDB, Hazelcast, BigQuery.
  • By far most employment needs are found in the SQL, VMware, Hadoop technologies.
  • These 3 fields have the most active practitioners who have the specific skill set or experience: SQL, Cloud computing, VMware.
  • VMware, SQL, JSON lead in searches for information online.
  • These three technologies are receiving the highest investments to gain clients: Managed private cloud, Cloud computing, Platform as a service.
  • These three technologies have the most active advertisers: Software developer, Cloud computing, Managed private cloud.
  • In patents, these three technologies have the most coverage ACID, GiST, SQL.
  • The most publications are available for VMware, Software developer, UniVerse.
  • Instruction and courseware availability is highest in these technologies: UniVerse, ACID, SQL.

The SAP HANA report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.

SAP HANA is an in-memory, column-oriented, relational database management system developed and marketed by SAP SE. Its primary function as database server is to store and retrieve data as requested by the applications.

The Predictive Analytics Scores below – ordered on Forecasted Future Needs and Demand from High to Low – shows you SAP HANA’s Predictive Analysis. The link takes you to a corresponding product in The Art of Service’s store to get started.

The Art of Service’s predictive model results enable businesses to discover and apply the most profitable technologies and applications, attracting the most profitable customers, and therefore helping maximize value from their investments. The Predictive Analytics algorithm evaluates and scores technologies and applications.

The platform monitors over ten thousand technologies and applications for months, looking for interest swings in a topic, concept, technology or application, not just a count of mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing it breaking into the mainstream. Data sources include trend data, employment data, employee skills data, and signals like advertising spent, advertisers, search-counts, Instruction and courseware available activity, patents, and books published.

Predictive Analytics Scores:

004840 – Predictive analytics
004486 – CAP theorem
000833 – NoSQL
000694 – Amazon Redshift
000637 – BigQuery
000627 – Vertica
000621 – Platform as a service
000609 – Apache Parquet
000608 – Hadoop
000436 – Query plan
000433 – Hazelcast
000391 – Redis
000378 – Microsoft Azure
000350 – Amazon Web Services
000343 – Cloud database
000323 – MemSQL
000321 – IaaS
000311 – JSON
000284 – Graph database
000275 – Greenplum
000263 – MariaDB
000246 – Apache Arrow
000238 – Apache Cassandra
000230 – SAP S/4HANA
000218 – Teradata
000217 – Inner join
000180 – Relational database management system
000169 – 1010data
000155 – Surrogate key
000151 – SQL Azure
000141 – Apache HBase
000137 – Oracle Exadata
000133 – Data Domain
000129 – Netezza
000129 – Foreign key
000118 – Managed private cloud
000117 – OLTP
000117 – Bluemix
000112 – Storage engine
000108 – UniVerse
000101 – VoltDB
000092 – Database management system
000086 – Outer join
000086 – FOSS
000081 – OpenEdge Database
000081 – EMC Corporation
000077 – Datablitz
000076 – Ehcache
000071 – Materialized view
000069 – Database server
000065 – ACID
000064 – Type system
000063 – GiST
000061 – Software developer
000052 – Pivotal Software
000051 – SQL
000049 – Zettabyte
000049 – XtraDB
000048 – Database model
000047 – VMware
000046 – Java DB
000043 – SQLite
000043 – R+ tree
000043 – Oracle Coherence
000043 – Namespace
000040 – Database trigger
000037 – MySQL Workbench
000036 – Sybase IQ
000034 – Omnis
000029 – SCADA
000024 – Unique key
000024 – IBM Power Systems
000020 – IBM i
000018 – Pervasive PSQL
000017 – Unicode
000014 – B+tree
000014 – B+ tree
000012 – Cloud computing
000007 – Google Fusion Tables
000006 – SAP ERP
000005 – SAP SE
000005 – LibreOffice
000000 – UnQLite
000000 – Tarantool
000000 – Reverse index
000000 – Raima
000000 – Query by Example
000000 – Partial index
000000 – MonetDB
000000 – Hash function
000000 – GPUdb
000000 – Gibibyte
000000 – Forest of Trees
000000 – Expression index
000000 – EXASOL
000000 – CUBRID
000000 – Boolean data type
000000 – Array data type
000000 – Apache license
000000 – Altibase


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