Name: Analytics Productivity for Overwhelmed Data Teams
Start: 2021-04-20T09:00:00Z
End: 2021-04-20T09:00:59.000Z
Location: BrightTALK
Rating: 5

Matillion is data transformation for cloud data warehouses. Only Matillion is purpose-built for Amazon Redshift, Snowflake, and Google BigQuery enabling businesses to achieve new levels of simplicity, speed, scale, and savings. Trusted by more than 800 companies to meet their data integration and transformation needs, Matillion products are highly rated across the AWS, GCP and Azure Marketplaces. Matillion is dual-headquartered in Manchester, UK and Denver, Colorado. Learn more about how you can unlock the potential of your data with Matillion’s cloud-based approach to data transformation.

Data infrastructure in the cloud presents unique opportunities for organizations to gain a competitive advantage - learn what sets the most successful Snowflake and Matillion customers apart.

Fireside Chat: Accelerating Data Workflows in the Cloud

Modern data teams are thinking far beyond traditional reporting to maximize their impact. They're employing low code/own code techniques and working hand in hand with data scientists to implement advanced analytics, make accurate predictions and ensure organizational resiliency.

Join Ciaran Dynes, Chief Product Officer at Matillion, and Adam Conway, SVP Products at Databricks, for this fireside chat as they talk about the future of data productivity and best practices for intelligent data pipelines.

Accelerating Data Productivity for Advanced Analytics & AI

Data professionals spend a whopping 64% of their time on data loading and prep. Learn how you can minimize the repetitive tasks involved in building and managing your data pipelines. Be free to code on your terms to build complex transformations and business logic.

Watch this session for a live demo of how to build and manage productive data pipelines via the low-code/no-code interface in Matillion ETL.

To code, or not to code? Optimize your time & boost the value of your data

Join Matthew Scullion, CEO at Matillion, Chris Degnan, Chief Revenue Officer at Snowflake, and Francisco Barroso, Principal of Data & AI Practice at Deloitte, for a Fireside Chat where they will discuss why data science and predictive analytics require a shift in perspective and can be a productivity multiplier - and what's coming next for data productivity.

Unlocking the Value of Data at Scale

Businesses today have to engage in a delicate balancing act between governance of data and speed of execution. As the volume, sources, and speed of data flowing into an organization continue to increase, it becomes harder for the data and compliance teams to properly catalog and track this important asset. To err on the side of caution creates a stranglehold on the amount of new data available for analytics, data science, and operational automation. Too lax of a stance, on the other hand, results in unsustainable exposure and risk.

Organizations have been chasing a way to automate the collection of data lineage and provenance for decades. But without tight integration across a number of tools and platforms, it has proved difficult to achieve. Join us for a fireside chat between Matillion Chief Product Officer, Ciaran Dynes, and Collibra VP of Product, Chandra Papudescu, to hear about the challenges organizations face and how better metadata sharing between partners provides the right balance between development speed and oversight.

Attend this fireside chat between Ciaran Dynes, Chief Product Officer at Matillion, and Chandra Papudesu, Vice President of Product Management at Collibra to learn more about:

- The inherent tension between the quality of data governance and the speed of data pipeline development
- How tighter, automated integrations between ETL and data catalog solutions can help organizations strike the right balance
- Details on Matillion and Collibra’s collaboration to help organizations deliver trusted and secured data at the pace their business demands

Fireside Chat: Deliver Trusted Data Faster with Automation

Change data capture (CDC) has long been a technology component complementing an on-premises enterprise reporting, business intelligence, and analytics program. By identifying modifications and updates to existing data sets, CDC helps to synchronize those updates by forwarding incremental changes to multiple downstream consuming applications, thereby reducing data latency, the need for bulk data transfers, and the disruption of batch data loading.

CDC performed in a traditional on-premises environment was largely performed behind the corporate firewall, soothing fears about inadvertent data exposure. However, as organizations modernize their data environments in the cloud, we begin to see risks of data exposure when change data capture is performed by products outside of the organization’s administrative control. In this webinar, we explore how modernization has opened the door for uncertainty in safely leveraging CDC, how CDC tools are evolving to support hybrid architectures, and how methods of encapsulation can help in governing change data capture.

Attendees will learn about:

- Change data capture basics
- How cloud modernization impacts CDC
- Capabilities of a modernized CDC process
- Characteristics of a CDC system to meet the needs of hybrid architectures

Governed Change Data Capture

Musti Group’s migration of their data environment to Snowflake in 2020 - 2021 had stalled due to the code-intensive complexity of their data integration and transformation solution. Their team did not have the bandwidth to move all of their data and build the business logic necessary for their needs, and the large amount of code required resulted in extensive processing within Snowflake, which prevented them from getting any results in a reasonable time and was also very costly. Musti decided to restart their Snowflake migration with Matillion from scratch in 2021 with exemplary results.

Attend this session and learn how Matillion helped Musti:
- Migrate over 10 data sources and business solutions with Matillion in just four months, enabling Musti to shut down their first cloud warehouse attempt and get  Musti’s cloud data platform migration back on track
- Optimise complex queries, fix errors, and greatly simplify business logic with Matillion’s visual low code/no-code approach
- Simplify the building of data pipelines and business logic, reducing Snowflake processing and costs to one-fifth of the starting point before Matillion
- Increased the amount of data available to the business by 3x, with plans to shorty increase by 10x

Optimising Snowflake Cloud Platform with Matillion

As companies move analytics to the cloud, they are often forced to balance between time spent manually gathering information about their data versus making that data useful as soon as possible. Luckily, today’s enterprises no longer have to compromise between governing data and iterating on it rapidly at cloud scale. By integrating an ETL solution with a data catalog, data teams can automate the capture of data lineage – where the data came from, how it was transformed - and greatly reduce their workloads while accelerating their ability to bring insights to the business.

Join us for this webinar with experts from Matillion and Zeenea and see how you can get started fast in the cloud without compromise:

- Find out about the data governance challenges facing organizations as they try to harness their vast and increasing data
- Learn about the advantages of cloud-native ETL and data catalog solutions – easy to deploy and maintain, extensible, flexible, future proof – for a modern data stack
- Discover how automating the input of data lineage metadata to a data catalog can reduce manual work and accelerate bringing trusted and governed data to the business
- See a live demonstration of the integration between Matillion ETL and Zeenea data catalog that makes this possible

Accelerate Cloud Data with Integrated ETL

Organizations that can actively harness data are 2.8 times more likely to post double-digit revenue growth. But given that the average enterprise analytics program wrestles with more than 1,000 different data sources, that’s easier said than done.

The inability of enterprises to extract and load data from databases, APIs, and other sources at speed and scale blocks them from using all of their data to make confident decisions faster. Most data integration solutions today are either fragmented and disconnected, or expensive and not built for the cloud.

Join us on May 24 for an exclusive launch event. Hear Matillion CEO Matthew Scullion, CPO Ciaran Dynes, and Matillion product leaders share why unifying data integration is critical to unblock and unlock your data to quickly make it useful. 

Give your team the tools and techniques they need to unlock the potential in their data today.

Data Unlocked: Unifying Data Integration in Modern Enterprises

Multiple aspects of cloud computing, from more scalability to increased flexibility in storage and compute to lower maintenance costs, are motivating organizations to develop a compelling business case for cloud modernization and migration. With all the benefits of the cloud, it is just a matter of time before most organizations will plan to migrate at least some aspect of their existing application and data landscapes to the cloud.

Yet despite the growing conventional wisdom favoring cloud migration, a smooth transition is unlikely without developing a tactical migration plan. In organizations with many siloed operations, it is valuable to have some well-defined processes for identifying and prioritizing candidate applications and data to migrate as well as simplifying the processes for migrating data to the cloud. At the same time, one must have a plan for mitigating resistance to changes in the enterprise data and application landscape.

In this webinar, we discuss practices and tactical steps that can alleviate some of the efforts of the cloud migration process. Attendees will learn about:

- Factors motivating cloud migration
- Organizational readiness assessment
- Criteria for prioritizing migration projects
- Leveraging automation in the cloud
- Simplifying development using no-code/low-code alternatives

Tactical Steps for Cloud Migration

Enterprise data teams are facing an influx of data from across the business, making it a real challenge to deliver rapid, actionable insights that are essential for competing in today’s digital economy. It’s becoming increasingly clear to enterprise data leaders that one way to handle this pressure is by extracting, migrating and transforming their data in the cloud. 

Leading to new insights that help make better business decisions, cloud-native data platforms in particular are transforming raw data into the refined, analytics-ready data that is imperative for supporting business growth. 

In this webinar, we’re joined by Simon Ratcliffe to discuss how cloud-native data integration can give companies a competitive edge and help them meet their business goals. From lessons learned at the beginning of a cloud-native data integration journey to successes the digital-first organization can expect, they'll be sharing:
 
- Considerations businesses need to take before starting their cloud-native data integration journey 
- What to look for in a cloud-native integration partner 
- The significant wins their cloud-native data integration journey has led them to
- Essential learnings from their cloud-native integration journey

Complete Cloud-Native Data Integration: Insights for Success

Although every organization has diverse data needs, they all have one challenge in common: business is moving faster than ever. In the stock market for example, an RPA bot can take only 5 milliseconds to respond to world news events with a trade. This real-time demand means that modern businesses that are seeking a competitive advantage have no choice but to harness their data to gain better business insights, quickly.  

One way to do this is to have a best-in-class DataOps strategy, and a cloud-powered DataOps strategy can make the world of difference - to your customers, your employees and to your bottom lines. 
In episode 3 of Matillion’s ‘Calming the Data Storm with the Cloud’ series, we’re bringing together DataOps leaders to share how businesses can use DataOps in the cloud to cope with data velocity demands and remain competitive.

We’ll be sharing:
- What DataOps is in the context of the cloud
- How to go from 0 to DataOps in a world of increasing customer demands
- What a winning DataOps strategy looks like and how can businesses expect to benefit
- Key considerations and

Defining a Cloud-Powered DataOps Strategy: Meeting Data Velocity Demands

The ability to create connected datasets is becoming one of the biggest competitive differentiators in enterprise operations. But with the rapid growth of data and the API economy, this is easier said than done. Today’s data teams must find an alternative to the limited selection of third-party connectors or hand-coding and maintaining connectors internally.

In this webinar, join Matillion to learn how leading enterprises are taking a different approach to long-tail data integration. Discover why open source isn’t the only way to achieve extensibility, and how a few simple changes can help you incorporate both batch and streaming data pipelines into your infrastructure today.

Bringing Universal Connectivity to Cloud Data Platforms

Are we there yet? Data was supposed to transform business as we know it. But the start of the New Year finds most data teams doing more busy work than ever just to keep up. Join Dave Langton, VP of Product at Matillion to learn how modern tools and architecture patterns can help you transcend data custodial tasks to focus on real innovation in analytics in 2021. 

Join us to learn: 
- The factors and events that shaped today’s data and analytics industry
- How to spot and diagnose the modern data challenges in your organization
- Practical strategies and solutions that leading data teams use to combat the overload

Analytics Productivity for Overwhelmed Data Teams

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Analytics Productivity for Overwhelmed Data Teams

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