Gartner Magic Quadrant for Data Quality Tools - 2019

Data quality is vital to achieving the most important and urgent digital business priorities. In Gartner’s 2018 CEO survey, 64% of respondents said they have management initiatives or transformation programs to make their business more digital (see “2018 CEO Survey: CIOs Should Guide Business Leaders Toward Deep-Discipline Digital Business”). The same survey found that CEOs expect digital revenue to grow by 10.3% between 2017 and 2020.

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

Informatica, SAP, IBM, SAS, Talend, Oracle, Syncsort are the leaders in "Gartner Magic Quadrant for Data Quality Tools - 2019".

The Forrester Wave™: Big Data NoSQL, Q1 2019

NoSQL covers a range of nonrelational databases, such as key-value, document, and graph databases, that are optimized for a new generation of business apps, including social media, customer 360, advanced insights, real-time, and operational apps. NoSQL vendors are delivering innovative features, such as AI and machine learning automation, integration with Apache Spark and streaming technology, support for SQL and simplified APIs, and extensive administrative tools.

Forrester defines big data NoSQL as:
A nonrelational database management system that provides storage, processing, and accessing of any type of data and which supports a horizontal, scale-out architecture based on a schemaless and flexible data model.

MongoDB, Microsoft (Azure Cosmos DB), Couchbase, AWS(DynamoDB), Google (Cloud Firestore), And Redis Labs Lead The Pack in "The Forrester Wave™: Big Data NoSQL, Q1 2019"

The Forrester Wave™: Master Data Management, Q1 2019

The first generation of MDM served to consolidate customer, product, or financial information across multiple systems of record, such as when M&A activity resulted in multiple enterprise resource planning  (ERP) systems. Data quality and compliance were the main features of first-generation MDM.

The internet of things has led to systems of automation and systems of design, which introduce new MDM usage scenarios to support co-design and the exchange of information on customers, products, and assets within ecosystems. This is ushering in a third generation of MDM for which flexibility, data virtualization, and data syndication are key, with more stakeholders involved in governing data.

Informatica, Reltio, And EnterWorks Lead The Pack in "The Forrester Wave™: Master Data Management, Q1 2019". Check out for Stibo, SAP, IBM ..etc

https://www.enterworks.com/resources/2019-forrester-wave-mdm/