The optimizer is one of the most complex parts of any data engine; it must ensure that the execution engine is performing at its best, so understanding how it works, is crucial.
This webinar deep dives into the various performance optimization techniques employed by Denodo’s Dynamic Query Optimizer and illustrates these techniques via a demonstration.
View this session to ensure that you achieve the maximum value from your data processing infrastructure:
Various components of query optimization engine
Different stages leveraged within the optimizer and the techniques applied.
When, how and why to use each option available in the query optimizer
Don’t miss the chance to discover Denodo’s Query Optimizer capabilities.
Check out this video to see how to create queries for dropdowns in your charts.
Good examples of this function would be query options for payment type, country, and city. It’s also important when changing dropdown query options that you update the filters for the main query that’s driving the visualization.
Presto is an open source distributed SQL engine, originally developed by Facebook for their massive Hadoop data warehouse. Treasure Data was one of the earliest adopters of Presto and, earlier this year, Teradata has joined the Presto community and announced a multi-year roadmap to accelerate Presto development to make it ready for enterprise users. This webinar will cover Presto architecture and discuss the technology behind the project.Read more >
Join us for this next segment of “Under the Hood” that focuses on the database designer feature of HPE Vertica.
Learn how the schema designs created by Database Designer provide optimal query performance for your most challenging analytic workloads. Database Designer uses smart strategies to create efficient schema designs that can be deployed, changed and re-deployed by almost anyone, even those without advanced database knowledge.
On Monday, 5 December, Euroclear Bank Settlement went live on the Taskize platform. Taskize is a new service that will help the financial services industry make work flow by enabling clients, colleagues and counterparties to address manual interventions efficiently, intelligently and securely.
In this 30-minute webinar, Luigi Bearzatto, Euroclear, joins Taskize Limited's John O'Hara and Philip Slavin to provide more detail on Taskize, its features, and the Euroclear-related offer that can be made available to you.
Earlier this year, the open source community delivered the Stinger Initiative to improve speed, scale, and SQL semantics in Apache Hive. Now Stinger.next is underway to build on those initial successes.
Join this 30-minute webinar with Hortonworks co-founder Alan Gates and Hortonworks Hive product manager Raj Baines to discuss SQL queries in HDP 2.2: ACID transactions and the cost based optimizer. You will also hear about the road ahead for the Stinger.next initiative.
Owen O’Malley and Carter Shanklin host the second of our seven "Discover HDP 2.1" webinars. They discuss the Stinger Initiative and the improvements to Apache Hive that are included in HDP 2.1: faster queries with Hive on Tez, new SQL semantics, and more.Read more >
IBM has taken query tuning to a new level with IBM Data Studio. More detail is available than ever before. However, the tool does take some getting used to, especially for folks that are used to a green screen based query tuning experience. This presentation introduces you to IBM Data Studio and gets you started tuning queries.Read more >
Join Rodney Landrum, Consulting Services Manager at Ntirety, a division of HOSTING, as he demonstrates his favorite features of the latest Microsoft SQL Server 2016 Service Pack 1.
During the webinar, Rodney will touch on the following:
• A demo of his favorite new features in SQL Server 2016 and SP1 including:
o Query Store
o Database Cloning
o Dynamic Data Masking
o Create or Alter
• A review of Enterprise features that are now available in standard edition
• New information in Dynamic Management Views and SQL Error Log that will make your DBA's job easier.
This video explores how applications connect to data sources and what that means to an embedded application.
Database query languages like Structured Query Language (SQL) and the Open Database Connectivity Protocol (ODBC) have been around a long time. SQL since the early 1970s and ODBC since 1986. And for as long as people have been querying data, reducing the length of time it took to get answers back -- query latency -- has been a problem. As databases have changed and new types emerged, solving the problem has become even more complex. Custom data source connectors are a solution.
Join Esther Spanjer, Director, Enterprise Business Development EMEA, for this webinar where she will discuss how SanDisk branded SSDs and HGST branded HDDs and SSDs are ideal for environments that run Hadoop databases. This webinar will look at cases where, SanDisk and HGST devices, can dramatically reduce query response times and minimize server sprawl by tuning compute and storage separately. Optimizing your Hadoop environment that suffer from queries that take too long to return data or in which applications are not meeting their SLAs, will enable you to reduce your server footprint at massively increased query performance.Read more >
This video will give you an idea of what features you should look for when choosing an embedded analytics technology.
First, of course, make sure it’s designed to be embedded. A lot of BI vendors out there peddle legacy technologies that have been retooled for embedding analytics -- with very mixed results.
Some other important capabilities include speed. Your embedded analytics technology should be fast. Users don’t want to watch a spinning hourglass while they wait minutes for query results. It should also natively accommodate modern data sources and make it easy to add new sources.
When your embedded technology has these and a few other essentials, it can keep up with the analytical demands of big data.
Check out this video for insight into big data access methods.
Spark SQL, Hive, and Hive QL offer different approaches to accessing data stored in Hadoop. The Hive alternatives are preferred by those accustomed to typical query languages. Amazon Redshift and Google BigQuery also have adherents in this corner of the big data space. Organization’s show data access preferences based on size and industry. Tech and financial services often adopt Spark SQL, but size plays into this dynamic. Smaller organizations tend to lean more towards Spark SQL, while larger organizations lean towards Hive and Hive QL even though they also show use of Spark SQL.
Content and Images Source: Dresner Advisory Services Big Data Analytics Market Study; Copyright 2017 -- Dresner Advisory Services
If you are working on an AI project, drop it. Chances are good that you don’t have AI problems (yet) but instead have data challenges. In this webinar, we will share what we learned from running a large data platform ingesting 2 million data points/sec and running 7 million queries for hundreds of enterprises. We will focus on the problems that you can tackle on Monday so that you are best positioned for next year and beyond.
About the presenter:
Kiyoto is VP of Marketing at Treasure Data. Previously, he was a Software Engineer at TrialPay and Trader at DRW Trading. He is a self-proclaimed hacker at heart: “creativity and do-ocracy over passivity and bureaucracy any day.”
What does it take to meet the challenges of ever growing big, fast data and modern data sources? Join us on May 11 at 10AM PST to find out!
Zoomdata’s Senior Director of Product Marketing Ian Fyfe and CTO Ruhollah Farchtchi will present the new capabilities of Zoomdata 2.5 and how they enable speed-of-thought visual analytics on massive data stores. Ian and Ruhollah will discuss Zoomdata’s:
- New data sharpening algorithm for large and long-running queries
- Enhanced memory management for very large result sets
- Drill to detail at scale capability
- Delegated security access
A demo featuring Zoomdata’s performance on a 10-billion row data set will follow the discussion. Register today.
With the drastic drop in the cost of sequencing a single genome, many organizations across biotechnology, pharmaceuticals, biomedical research, and agriculture have begun to make use of genome sequencing. While the sequence of a single genome may provide insight about the individual who was sequenced, to derive maximal insight from the genomic data, the ultimate goal is to query across a cohort of many hundreds to thousands of individuals.
Join this webinar to learn how Databricks — powered by Apache Spark — enables queries across a database of genomics in interactive time and simplifies the application of machine learning models and statistical tests to genomics data across patients, to derive more insight into the biological processes driven by genomic alterations.
In this webinar, we will:
- Demonstrate how Databricks can rapidly query annotated variants across a cohort of 1,000 samples.
- Look at a case study using Databricks to improve the performance of running an expression quantitative trait loci (eQTL) test across samples from the GEUVADIS project.
- Show how we can parallelize conventional genomics tools using Databricks.
Microservices may be small in size, but they have huge potential, especially when you pair them with the idea of event-driven architecture (EDA). Today developers are using microservices as the building blocks behind all kinds of cloud and enterprise applications, but most still think microservices = REST, which limits you to polling/reactive interactions.
Join Jonathan Schabowsky of Solace’s Office of the CTO at Solace as he describes how combining EDA and microservices can help you improve all kinds of data flows. He’ll talk about query and command interactions, synchronous and asynchronous communications, and you’ll learn how to make microservices event-driven.
The HSBC GIF Asia ex Japan Equity Smaller Companies fund continued its strong run as it delivered a total return of 23% for the first six months of the year, and remained in the first quartile among its competitors for 3-month, 6-month, 1-year and 3-year periods.
In her second quarterly update webcast, Elina Fung, lead manager of the fund, will share the latest strategy and positioning of the fund. On this call, Elina will also answer questions from clients, so please free to email your queries to your local sales representative or you can also ask the questions live during the webcast.
No Code, Low Code Big Data Analytics from Simple Search to Complex Event Processing.
Logtrust is designed for fast data exploration and interaction with real-time visualizations on complex data streams and historical data at rest such as:
- Machine behavior during attacks
- Network traffic flow analytics
- Firewall events
- Application performance metrics
- Real-time threat hunting and cyber security
- IoT analytics
Explore Petabytes of data with Logtrust without worrying about storage costs or indexers, analyze billions of events per day with ultra-low latency queries, and experience unique real-time performance on trillions of events with over +150,000 ingest EPS per core, +1,000,000 search EPS per core, and +65,000 complex event processing EPS per core.
Live Data Exploration
Logtrust data is always fresh with real-time data updates in their native formats. Slice and dice subsets of data at any point in time for exploration and deep forensics on real-time data streams.
Powerful Data Exploration & Analytics
Accelerate time-to-insights and rich visualizations with simple point and click. Empower your team to quickly harness insights and make faster, smarter decisions. Optionally, use a single compact expressive SQL language (LINQ) and create reusable callable queries for more complex event processing operations.
Part three in a five-part series, this webcast will be a demonstration of the integration of Hortonworks HDB and Apache Hadoop YARN. YARN provides the global resource management for HDB for cluster-level hardware efficiency, while the in-database resource queues and operators provide the database and query-level resource management for workload prioritization and query optimization. This webinar will focus on demonstrating the installation process as well as discuss the various YARN and HDB parameters and best practice settings.Read more >
SQL injection attacks enable attackers to tamper with, delete or steal sensitive data from corporate databases. In this webinar, Zach Jones, senior manager for static code analysis from WhiteHat Security’s Threat Research Center, will discuss SQL injection attacks and how to best defend against them.
In this webinar, we will:
- Provide examples of vulnerable code
- Discuss data boundary concepts between input and target interpreters
- Explain the differences and advantages of using parameterized queries versus custom stored procedures
- Discuss the pitfalls of using selective parameterization or trying to sanitize inputs by escaping or encoding them manually
WhiteHat Security has extensive experience working with customers to identify and fix the latest web application vulnerabilities. Join us to gain a deeper understanding of common web application vulnerabilities, get expert technical advice on defensive tactics, and learn best practices to safeguard your apps from being exploited.
Learn how compliance leaders at global banks are using CDL, the cybersecurity data lake, to unlock the power of existing siloed products and systems (Qualys, FireEye, Conventus, etc.) to enhance, extend and create new advanced analytics, queries and visualization from siloed data.
This webinar will cover:
- New compliance architecture for unlocking siloed cybersecurity.
- New compliance use cases for banks and digital businesses.
- How banks are using CDL to develop next-generation compliance
Analysing big data quickly and efficiently requires a data warehouse optimised to handle and scale for large datasets. Amazon Redshift is a fast, petabyte-scale data warehouse that makes it simple and cost-effective to analyse big data for a fraction of the cost of traditional data warehouses. By following a few best practices, you can take advantage of Amazon Redshift’s columnar technology and parallel processing capabilities to minimize I/O and deliver high throughput and query performance. This webinar will cover techniques to load data efficiently, design optimal schemas and tune query and database performance.
• Get an inside look at Amazon Redshift's columnar technology and parallel processing capabilities
• Learn how to migrate from existing data warehouses, optimise schemas and load data efficiently
• Learn best practices for managing workload, tuning your queries and using Amazon Redshift's interleaved sorting features
Who Should Attend:
• Data Warehouse Developers, Big Data Architects, BI Managers and Data Engineers
Other sessions on the AWS Big Data Webinar Day - 28 September:
10:00 - 11:00 GMT | Getting Started with Big Data on AWS
Register » https://www.brighttalk.com/webcast/9019/221047?utm_campaign=Brighttalk
11:15 - 12:15 GMT | Architectural Patterns for Big Data on AWS
Register » https://www.brighttalk.com/webcast/9019/221063?utm_campaign=Brighttalk
12:30 - 13:30 GMT | Building Big Data Solutions with Amazon EMR and Amazon Redshift
Register » https://www.brighttalk.com/webcast/9019/221145?utm_campaign=Brighttalk
Join this webinar to learn:
1. What is Power BI?
a. More power to Business Inteligence
2. Why Power BI?
a. Which data sources we can connect and analyse with Power BI?
b. How to connect those data sources to Power BI?
c. What is the role of R as a data source?
d. How to visualise and Analyse?
i. Design skills
ii. Tips and tricks
iii. Analytics patterns
1. Custom visuals
2. R Custom visuals (Predictive Analytics)
4. What about Backend Management?
a. Excel / Azure SQL / Azure Storage or Other
b. Custom Tables / Columns / Measures
i. What / Why / How?
5. Power BI Updates
b. Power BI Community for queries and request/issues updates
i. How to use this?