Business intelligence
Analyze data to gain actionable insights and improve decision making for your business
Data management software and solutions
Promote agility and efficiency with end-to-end data management
Overview
Data management for agility and efficiency
Today, data is even more distributed than ever requiring supporting technologies to evolve and new solutions to address current data management issues in innovative and unprecedented ways. Data management is designed to help you achieve consistent access to and delivery of data across all data structures and subject areas in your enterprise. Applying a comprehensive data management plan helps meet data consumption requirements of all applications and business processes.
Additionally, a data fabric approach simplifies access and facilitates self-service data consumption that is independent of environment, process, utility and geography. A data fabric enables enterprises to automate data usage to maximize their value chain.
ADMINN22 data management empowers businesses to improve outcomes using any data for analytics or applications across any cloud including on-premises, public and private. Gain resiliency, reliability, scalability and availability with security and quality with IBM, and get more from multimodal, multicloud data ecosystems to increase your enterprise readiness for data management.
Benefits
Why ADMINN22 for data management
ADMINN22 data management helps improve outcomes by using any data for analytics or applications across any cloud and helps you automate end-to-end data management.
Promote agility and efficiency
Harness data for modern apps, analytics, and AI. Spot new patterns and trends to improve operations and create new offerings.
Simplify and unify data tiers
Get value from any transactional, operational and analytical data. Access structured and unstructured data in real-time and batch.
Help ensure resiliency, reliability, and scalability
Promote business continuity and mitigate data-related outages. Start small and scale across use cases and deployments.
Meet governance, risk, compliance, and sustainability objectives
Take a data-driven approach to meeting regulatory, corporate and environment mandates. Protect data privacy and security end-to-end.
Automate and govern your data
Reduce complexity and speed time to value through automated data management. Improve decision-making and act on insights faster with AI-powered self-service.
Speed deployment and avoid lock-ins
Partner with ADMINN22 to manage data ecosystems. Implement business analytics and conversational AI faster in a data fabric architecture.
Data management solutions
Database management
Employ high-performance and scalable transactional processing with query optimization.
Data warehouse
Perform analytics with on-premises, cloud and integrated appliance deployment options.
Data lake
Store and query structured, semi-structured and unstructured data.
Introduction
What is business intelligence?
Business intelligence (BI) is an umbrella term for the technology that enables data preparation, data mining, data management, and data visualization. Business intelligence tools and processes allow end users to identify actionable information from raw data, facilitating data-driven decision-making within organizations across various industries.
There are a number of BI tools in the marketplace, which aid business users in analyzing performance metrics and extracting insights in real time. These tools focus on self-service capabilities, reducing IT dependencies and enabling decision-makers to recognize performance gaps, market trends, or new revenue opportunities more quickly. BI applications are commonly used to make informed business decisions, advancing a company’s position within the marketplace.
User adoption of BI software continues to increase at a rapid pace, especially as customers migrate workloads to the cloud. Vendors are increasingly supportive of different cloud platform providers, leading to more SaaS-based BI solutions and subscription-based pricing models.
BI versus business analytics
Business intelligence versus business analytics
The term business intelligence is commonly used in association with business analytics, and while there is significant overlap between the two areas, business intelligence focuses more narrowly on what is happening in your business and why, while business analytics more broadly includes solutions that help you leverage that insight to plan for the future. Business intelligence uses descriptive analytics to formulate conclusions about historical and current performance, providing context around changes in key performance indicators (KPIs).
Business analytics and business intelligence are inclusive of prescriptive and predictive analytics practices, which help advise decision-makers on potential future outcomes. Both BI and business analytics solutions enable stakeholders to make better decisions, and these should be viewed as complementary to one another.
Business analytics and data analytics tend to be used interchangeably. But business analytics is a merely a subset of data analytics, as the scope of data analytics can refer to any analysis of data. Business analytics focuses on discovering information which can improve business decision-making.
Data governance tools and solutions
Understand and govern all enterprise data to mitigate risk and accelerate insights
Overview
Why employ data governance solutions?
Data governance solutions and tools provide understanding, security and trust around an organization’s data. As companies scale and accumulate more data sources and assets, they must determine the appropriate big data environments for storage and access purposes. They need architecture to govern sources, integrate them and make them available across an organization. Data integration becomes increasingly important as it impacts the workflows and decision-making of various teams.
Employ data governance tools to your overall strategy for data management and as part of a complete DataOps practice. Data governance solutions help you understand what data you have, where that data resides and how it can be used.
Benefits
Benefits of data governance tools
Achieve deeper insights while protecting data with strong data governance practices.
Better data security and compliance
With the rise of data-driven marketing and remote work, compliance regulations are increasingly prevalent. Use data governance to promote security and compliance, and reduce the risk of breaches and fines.
Improved data quality
Business intelligence tools are only as good as the data that feeds them. Data governance helps connect information across systems and identify meaningful relationships to get the most out of an organization’s data.
Faster automation
Data governance practice helps ensure accurate and protected customer data. As a result, analytics teams can innovate and automate specific tasks with machine learning algorithms, achieving greater growth and more targeted selling.
Data science and AI
Build and scale AI with trust and transparency
Overview
Fuel your journey to AI with data science
Build and scale AI with trust and transparency to drive digital transformation, deliver personalized customer experiences and make more data-backed decisions.
Accelerate time to value with visual data science tools.
Track and measure outcomes from AI across its lifecycle.
Adapt and govern AI quickly to changing business situations.
Optimize business outcomes with prescriptive analytics.
Debias AI with transparency and explainability.
Solutions
Data science
Extract data insights using AI, machine learning and automation across the data science lifecycle.
Predictive analytics
Predict future outcomes using a flexible, scalable platform for data analysis and model building.
Decision optimization
Transform business decision-making with a family of optimization products.