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Business Intelligence (BI) tools facilitate improved decision making by enabling users to access and analyze data in an efficient and intuitive manner. 

Analytics tools enable organizations to make the most of their big data and maximize the results of their big data strategy.

Modern big data integration often requires rapid ingestion of data from varied sources, while minimizing the impact of their performance.

A blockchain is a distributed ledger that serves as a historical record of a set of transactions.

Business intelligence (BI) enhances decision making by giving stakeholders the ability to tap into enterprise information assets.

Cloud solutions provide many benefits over traditional infrastructure , such as improved performance, lower upfront investment, and greater flexibility and scalability to handle growth and unantici

Dashboards provide a single point of access to various types of BI content, including reports, metrics, KPIs, and visualizations. 

Data analysis tools make it easier for users to sort through enterprise data in order to identify patterns, trends, relationships, correlations, and anomalies that would otherwise be difficult to d

Data Analytics transforms your data into actionable information by combining multiple sources of internal and external data.

Data discovery allows business users to interact with enterprise data visually to uncover hidden patterns and trends.

Data governance encompasses every kind of policy related to an organization’s data, including its use, distribution, metric definitions, retention, security, and access.

Data integration solutions gather and unify data from heterogeneous information sources that reside both within and outside the enterprise. 

Data integrity solutions greatly improve the completeness and accuracy of data from enterprise sources.

Data management is a strategy for overseeing all the information housed by your organization -- especially in the light of IoT, big data, and other advanced initiatives. 

Data profiling includes the collection, aggregation, and examination of enterprise information, to gather statistics and details about it.

Data quality is a top priority for today’s organizations, determining the integrity of enterprise information. 

Data quality management (DQM) has increased in importance as information infrastructures become more sophisticated and the volume of data generated continues to expand rapidly. 

Data visualization solutions display information in easy-to-read charts, maps, plots, and graphs, to help business users rapidly identify patterns and trends and detect anomalies.

A data warehouse is a repository that presents an aggregated view of enterprise data, optimized for BI and analytics. 

Decision support systems improve operational efficiency and business performance by enhancing the ability of stakeholders to make faster, smarter decisions based on information, rather than gut ins

With extract, transform, and load (ETL) tools, organizations can extract data from disparate databases, applications and systems, transform it as appropriate, and load it into another database.

Healthcare analytics enables users to make sense of the morass of clinical, financial, operational, and provider data that is generated each day.

Consumers are data-driven, demanding real-time information in the context of their current activities. 

Information delivery solutions are designed to meet growing demands for “anytime, anywhere” access to enterprise data by making it easier to share more information with more people—executives, mana

The Internet of Things (IoT) uses sensors and high-speed communications to connect millions of devices for virtually any purpose you can think of.

Master data management (MDM) consists of practices, processes, and technologies for ensuring the consistency and accuracy of data across multiple sources.

Predictive analytics empowers business users to anticipate future events, behaviors, and conditions based on the historical information contained in enterprise systems.

Predictive maintenance is usually driven by sensors that collect data about specific pieces of equipment being maintained, after which analytics can show when maintenance is most likely to be usefu