Few trends have had a bigger impact on the data platforms landscape than the emergence of cloud computing. The adoption of cloud computing infrastructure as an alternative to on-premises datacenters has resulted in significant workloads being migrated to the cloud, displacing traditional server and storage vendors. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research currently use cloud computing products for analytics and data, and a further...
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Topics:
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data
Organizations today are working with multiple applications and systems, including enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) and other systems, where data can easily become fragmented and siloed. And as the organization increases its data sources and adds more systems and custom applications, it becomes challenging to manage the data consistently and keep data definitions up to date. This increases the need to use master data...
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Topics:
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data,
Digital Technology,
Analytics & Data
Pricing is an issue that almost every for-profit company confronts – and usually agonizes over. Chief financial officers must play a part in setting the strategic direction of pricing in their organization. They should not be involved in tactical pricing decisions because they are not close enough to markets and customers, but they should be part of the strategic design of pricing, especially as part of a profitability management effort, which I’ve discussed before.
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Topics:
Office of Finance,
Analytics,
Financial Performance Management,
Digital Commerce,
Digital Business,
Revenue Management,
Sales Engagement
The need for data-driven decision-making requires organizations to transform not only the approach to business intelligence and data science but also accelerate the development of new operational applications that support greater business agility, enable cloud- and mobile-based consumption, and deliver more interactive and personalized experiences. To stay competitive, organizations need to prioritize the development of new, data-driven applications. As a result, many have been encouraged to...
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Topics:
Analytics,
Cloud Computing,
Analytics & Data
The term NoSQL has been a misnomer ever since it appeared in 2009 to describe a group of emerging databases. It was true that a lack of support for Structured Query Language (SQL) was common to the various databases referred to as NoSQL. However, it was always one of a number of common characteristics, including flexible schema, distributed data processing, open source licensing, and the use of non-relational data models (key value, document, graph) rather than relational tables. As the various...
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Topics:
Business Continuity,
Analytics,
Data,
Digital Technology,
Digital Business,
data platforms
Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes,
data operations,
data platforms,
AI and Machine Learning
As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...
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Topics:
business intelligence,
Analytics,
Data,
data lakes,
data operations,
data platforms,
AI and Machine Learning
Any organization that relies heavily on a large labor force looks to automation to reduce costs, and contact centers are no exception. They handle interactions at such large scale that almost any effort to automate some part of the process can deliver measurable efficiencies. Two factors have ratcheted up attention on automating customer experience workflows: the dramatic expansion of digital interaction channels, and the development of artificial intelligence and machine learning tools to...
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Topics:
Customer Experience,
Voice of the Customer,
Analytics,
Data Integration,
Contact Center,
Data,
agent management,
data operations,
Digital Business,
Experience Management,
Customer Experience Management,
Field Service,
AI and Machine Learning
TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management...
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Topics:
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Information Management,
Data,
Digital Technology,
data lakes,
AI and Machine Learning
Organizations have become more agile and responsive, in part, as a result of being more agile with their information technology. Adopting a DevOps approach to application deployment has allowed organizations to deploy new and revised applications more quickly. DataOps is enabling organizations to be more agile in their data processes. As organizations are embracing artificial intelligence (AI) and machine learning (ML), they are recognizing the need to adopt MLOps. The same desire for agility...
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Topics:
business intelligence,
Analytics,
Data Governance,
Data,
Digital Technology,
data operations,
data platforms