Gartner Magic Quadrant for Data Integration Tools 2020

 "By 2023, organizations utilizing data fabrics to dynamically connect, optimize and automate data management processes will reduce time to integrated data delivery by 30%. Through 2025, over 80% of organizations will use more than one cloud service provider (CSP) for their data and analytics use cases, making it critical for them to prioritize an independent and CSP-neutral integration technology to avoid vendor lock-ins."

15th straight year, Informatica has been named a Leader in the Gartner Magic Quadrant for Data Integration Tools.

Informatica, IBM, SAP, Oracle, Talend, SAS and Denodo are the leaders in "Gartner Magic Quadrant for Data Integration Tools 2020"

Magic Quadrant for Data Quality Solutions 2020

 By 2022, 60% of organizations will leverage machine-learning-enabled data quality technology for suggestions to reduce manual tasks for data quality improvement.

Market Definition: The term “data quality” relates to the processes and technologies for identifying, understanding and correcting flaws in data that support effective data and analytics governance across operational business processes and decision making. The packaged solutions available include a range of critical functions, such as profiling, parsing, standardization, cleansing, matching, enrichment, monitoring and collaborating.

Informatica, IBM, SAP, SAS, Talend & Precisely are the leaders in "Magic Quadrant for Data Quality Solutions 2020".

The Forrester Wave™: Enterprise Data Fabric, Q2 2020

Data fabric focuses on automating the process integration, transformation, preparation, curation, security, governance, and orchestration to enable analytics and insights quickly for business success. It minimizes complexity by automating processes, workflows, and pipelines, generating code and streamlining data to accelerate various use cases such as customer 360, data science, fraud detection, internet-of-things (IoT) analytics, risk analytics, and healthcare insights.

AI/ML, Self-Service, And Graph Engine Are Key Differentiators

Oracle, Talend, Cambridge Semantics, SAP, Denodo, And IBM Lead The Pack in "The Forrester Wave™: Enterprise Data Fabric, Q2 2020".

2020 Magic Quadrant for the CRM Customer Engagement Center

By 2023, 30% of customer service organizations will deliver proactive customer service using artificial intelligence (AI), process orchestration and continuous intelligence.

Gartner’s Definition: The current reshaping of the customer engagement center (CEC) market is characteristic of the consolidation of the customer service technology market. Customer service and support organizations must deliver consistent, effortless, intelligent and personalized customer service to their customers. The ability to orchestrate customer requests with assisted service, as well as with self-service, is one of the four pillars of great customer service within a leading customer service and support operation.

The four pillars of great customer service are:

1.    Getting connected

2.    Process orchestration

3.    Resource management

4.     Analytics and insights

Salesforce, Pegasystems, Servicenow, Microsoft, Oracle & Zendesk are the leaders in 2020 Magic Quadrant for the CRM Customer Engagement Center

2020 Magic Quadrant for Multichannel Marketing Hubs

Digital marketing leaders use multichannel marketing hubs to orchestrate contextually relevant experiences across complex journeys. Marketing leaders remain focused on driving more relevant digital experiences across the customer journey. 

Gartner defines the multichannel marketing hub (MMH) as a technology that orchestrates a company’s communications with and offers to customer segments across multiple channels. These include websites, mobile, social, direct mail, call centers, digital advertising and email. MMH capabilities also may extend to integrating marketing offers and leads with sales for execution in both B2B and B2C environments.

Adobe, Salesforce, SAS, Acoustic, SAP are the leaders in “2020 Magic Quadrant for Multichannel Marketing Hubs”.

2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms

Expert data scientists and other professionals working in data science roles require capabilities to source data, build models and operationalize machine learning insights.

The DSML (Data Science and Machine Learning Platforms)  platform offers a mixture of basic and advanced functionality essential for building DSML solutions (primarily predictive and prescriptive models). The platform also supports the incorporation of these solutions into business processes, surrounding infrastructure, products and applications. It supports variously skilled data scientists in multiple tasks across the data and analytics pipeline, including all of the following areas:

• Data ingestion
• Data preparation
• Data exploration
• Feature engineering
• Model creation and training
• Model testing
• Deployment
• Monitoring
• Maintenance
• Collaboration

SAS, Databricks, Tibco, DataIku, Alteryx and MathWorks are the leaders in "2020 Gartner Magic Quadrant for Data Science and Machine Learning Platforms"

Magic Quadrant for Analytics and Business Intelligence Platforms 2020

Augmented capabilities are becoming key differentiators for analytics and BI platforms, at a time when cloud ecosystems are also influencing selection decisions.

By 2022, augmented analytics technology will be ubiquitous, but only 10% of analysts will use its full potential.

Modern analytics and business intelligence (ABI) platforms are characterized by easy-to-use functionality that supports a full analytic workflow — from data preparation to visual exploration and insight generation — with an emphasis on self-service and augmentation.

Microsoft (PowerBI), Tableau, Qlik and ThoutSpot are the leaders in "Magic Quadrant for Analytics and Business Intelligence Platforms 2020"