Introduction to SQL Server 2019

Argon Systems

Modern enterprises are struggling to gain insights from an exploding number of database management systems and ever-growing data volumes. SQL Server 2019 can help you overcome the challenges of integrating data and bring AI and machine learning to all of your data, structured and unstructured. It can also help you better manage your relational data right now. In this webinar, Introduction to SQL Server 2019, hear from Debbi Lyons, Senior Product Marketing Manager, Travis Wright, Principal Program Manager, and Bob Ward, Principal Architect at Microsoft discuss the latest updates and features for the new SQL Server release, including introducing the new big data cluster with intelligence over any data, how SQL Server 2019 enhances the developer experience, and using tools including Azure Data Studio.
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Spotlight

Affective computing and sentiment analysis, hence, are key for the advancement of AI3 and all the research fi elds that stem from it. Moreover, they fi nd applications in various scenarios and companies, large and small, that include the analysis of emotions and sentiments as part of their mission. Sentiment-mining techniques can be exploited for the creation and automated upkeep of review and opinion aggregation websites.

OTHER ON-DEMAND WEBINARS

How to Modernize Data Lake Technologies with Cloud-Based Solutions

tdwi.org

Data lakes based on Hadoop technologies have proved themselves valuable in mission-critical use cases such as data warehousing, advanced analytics, multichannel marketing, complete customer views, digital supply chains, and the modernization of data management.Most Hadoop users are committed to the data lake method of managing data, but they are limited by Hadoop shortcomings in key areas such as cluster maintenance, administration cost, resource management, metadata management, and support for SQL and other relational technologies. Many view cloud-based solutions as the optimal replacement for their data lake, but they are not ready to make such a significant change. The truth is: they don't have to, as the two technologies can coexist.
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Streaming Data: The Nexus of Cloud-Modernized Analytics

Leveraging business data as a valuable asset is no longer a debated concept – it’s a broadly adopted, competitive undertaking that’s part and parcel to cloud modernization. Today, if there’s one thing that defines competitive advantage in the data analytics arena it’s streaming data platforms. Older approaches employing batch-only analytics, brittle ETL pipelines, and the latency they can introduce just don’t cut it anymore. Cloud-Modernized Analytics are poised to step in and take over.
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A Complete Set of Data Governance Roles & Responsibilities

KIK Consulting

Roles and responsibilities are the backbone to a successful Data Governance program. The way you define and utilize the roles will be the biggest factor of program success. From Data Stewards to the steering committee and everyone in between, people will need to understand the role they play, why they are in the role and how the role fits in with their existing job. Join Bob Seiner for this RWDG webinar where he will provide a complete and detailed set of Data Governance roles and responsibilities. Bob will share an Operating Model of Roles and Responsibilities that can be customized to address the specific needs of your organization
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Augmenting BI and Analytics in the Age of AI and Big Data

Arcadia Data

Artificial intelligence (AI) and big data technologies are driving major changes in how organizations think about business intelligence and analytics. Rather than be limited to querying and reporting on just what is in traditional BI systems or data warehouses, many business users and analysts want to tap a fuller range of data in systems running Apache Hadoop, Apache Spark, or on cloud data platforms and storage. At the same time, AI practices and technologies (in particular machine learning and natural language processing) are changing how users explore, analyze, and interact with data and the types of insights they can generate.
Watch Now

Spotlight

Affective computing and sentiment analysis, hence, are key for the advancement of AI3 and all the research fi elds that stem from it. Moreover, they fi nd applications in various scenarios and companies, large and small, that include the analysis of emotions and sentiments as part of their mission. Sentiment-mining techniques can be exploited for the creation and automated upkeep of review and opinion aggregation websites.

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