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Mar 22 2024
Strategies for Midsize Enterprises to Overcome Cloud Adoption Challenges

While moving to the cloud is transformative for businesses, the reality is that midsize enterprise CIOs and CDOs must consider a number of challenges associated with cloud adoption. Here are the three most pressing challenges we hear about – and how you can work to solve them.

  • Leveraging existing data infrastructure investments
  • Closing technical skills gap
  • Cloud cost visibility and control

Recommendations

  • Innovate with secure hybrid cloud solutions
  • Choose managed services that align with the technical ability of your data team
  • Maintain cost control with a more streamlined data stack

Innovate With Secure Hybrid Cloud Solutions

There is no denying that cloud is cheaper in the long run. The elimination of CapExcosts enables CIOs to allocate resources strategically, enhance financial predictability, and align IT spending with business goals. This shift toward OpEx-based models is integral to modernizing IT operations and supporting organizational growth and agility in today’s digital economy.

Data pyramid on the data cloud in 2028

But migrating all workloads to the cloud in a single step carries inherent risks including potential disruptions. Moreover, companies with strict data sovereignty requirements or regulatory obligations may need to retain certain data on-premises due to legal, security, or privacy considerations. Hybrid cloud mitigates these risks by enabling companies to migrate gradually, validate deployments, and address issues iteratively, without impacting critical business operations. It offers a pragmatic approach for midsize enterprises seeking to migrate to the cloud while leveraging their existing data infrastructure investments.

How Actian Hybrid Data Integration Can Help

The Actian Data Platform combines the benefits of on-premises infrastructure with the scalability and elasticity of the cloud for analytic workloads. Facilitating seamless integration between on-premises data sources and the cloud data warehouse, the platform enables companies to build hybrid cloud data pipelines that span both environments. This integration simplifies data movement, storage and analysis, enabling organizations to extend the lifespan of existing assets and deliver a cohesive, unified and resilient data infrastructure. To learn more read the ebook 8 Key Reasons to Consider a Hybrid Data Integration Solution

Choose Managed Services That Align With the Technical Ability of Your Data Team

Cloud brings an array of new opportunities to the table, but the cloud skills gap remains a problem. High demand means there’s fierce market competition for skilled technical workers. Midsize enterprises across industries and geos are struggling to hire and retain top talent in the areas of cloud architecture, operations, security, and governance, which in turn severely delays their cloud adoption, migration, and maturity. This carries the potential greater risk of falling behind competitors.

Data Analytics on cloud skills

Bridging this skills gap requires strategic investments in HR and Learning and Development (L&D), but the long-term solution has to go simply beyond upskilling employees. One such answer is managed services that are typically low- or no-code, thus enabling even non-IT users to automate key BI, reporting, and analytic workloads with proper oversight and accountability. Managed solutions are typically designed to handle large volumes of data and scale seamlessly as data volumes grow—perfect for midsize enterprises. They often leverage distributed processing frameworks and cloud infrastructure to ensure high performance and reliability, even with complex data pipelines.

Actian’s Low-Code Solutions

The Actian Data Platform was built for collaboration and governance midsize enterprises demand. The platform comes with more than 200 fully managed pre-built connectors to popular data sources such as databases, cloud storage, APIs, and applications. These connectors eliminate the need for manual coding to interact with different data systems, speeding up the integration process and reducing the likelihood of errors. The platform also includes built-in tools for data transformation, cleansing, and enrichment. Citizen integrators and business analysts can apply various transformations to the data as it flows through the pipeline, such as filtering, aggregating and cleansing, ensuring data quality and reliability—all without code.

Maintain Cost Control with a More Streamlined Data Stack

Midsize enterprises are rethinking their data landscape to reduce cloud modernization complexity and drive clear accountability for costs across their technology stack. This complexity arises due to various factors, including the need to refactor legacy applications, integrate with existing on-premises systems, manage hybrid cloud environments, address security and compliance requirements, and ensure minimal disruption to business operations.

Point solutions, while helpful for specific problems, can lead to increased operational overhead, reduced data quality, and potential points of failure, increasing the risk of data breaches and regulatory violations. Although the cost of entry is low, the ongoing support, maintenance, and interoperability cost of these solutions are almost always high.

Data Analytics on Top Cloud Challenges

A successful journey to cloud requires organizations to adopt a more holistic approach to data management, with a focus on leveraging data across the entire organization’s ecosystem. Data platforms can simplify data infrastructure, thus enabling organizations to migrate and modernize their data systems faster and more effectively in cloud-native environments all while reducing licensing costs and streamlining maintenance and support.

How Actian’s Unified Platform Can Help

The Actian Data Platform can unlock the full potential of the cloud and offers several advantages over multiple point solutions with its centralized and unified environment for managing all aspects of the data journey from collection through to analysis. The platform reduces the learning curve for users, enabling them to derive greater value from their data assets while reducing complexity, improving governance, and driving efficiency and cost savings.

Getting Started

The best way for data teams to get started is with a free trial of the Actian Data Platform. From there, you can load your own data and explore what’s possible within the platform. Alternatively, book a demo to see how Actian can accelerate your journey to the cloud in a governed, scalable, and price-performant way.

The post Strategies for Midsize Enterprises to Overcome Cloud Adoption Challenges appeared first on Actian.


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Author: Dee Radh

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Jan 18 2024
Digital Transformation: Modernizing Database Applications

In my previous blog on digital transformation, I wrote about the benefits of migrating mission-critical databases to the cloud. This time, I’m focusing on modernizing the applications that interact with the database. Application modernization can involve modernizing an application’s code, features, architecture and/or infrastructure. It’s a growing priority according to The 2023 Gartner CIO and Technology Executive Survey that places it in the top 4 technology areas in spending, with 46% of organizations increasing their spend on application modernization. Further, Foundry, an IDG company, reports that 87% of its survey respondents cite modernizing critical applications as a key success driver.

7 Benefits of Database Application Modernization

Why all the recent interest in transitioning to modern applications? Application modernization and database modernization are closely intertwined processes that work together to enhance the overall agility, efficiency, performance, security, innovation, and capabilities of an organization’s business. Here’s how application modernization complements database modernization:

Accelerated Time to Market

Monolithic legacy applications are time consuming to update. Modernized applications with a loosely coupled architecture can enable faster development cycles, reducing the time it takes to bring new features or products to market. Agile development methodologies often accompany application modernization, enabling incremental and iterative development so that teams can respond rapidly to changing business requirements.

Cloud-Enabled Opportunities

Moving applications to the cloud as part of an application modernization initiative provides an extensive list of advantages over on-premises deployments, including elasticity, scalability, accessibility, business continuity, environmental sustainability, a pay-as-you-go model, and more.

Optimized User Experience

Modernizing applications offers many ways to increase user satisfaction, and productivity, including more intuitive interfaces, personalization, improved response times and better accessibility.  Multi-channel support such as mobile and web and cross-platform compatibility extend reach while advanced search and navigation, rich media incorporation, and third-party integrations add value for users.

Stronger Security and Compliance

Legacy applications built on outdated technologies may lack security features and defenses against contemporary threats and may not comply with regulatory compliance requirements. Modernizing applications allows for the implementation of the latest security measures and compliance standards, reducing the likelihood of security breaches and non-compliance.

Staff Productivity

Legacy systems can be difficult to maintain and may require significant technical resources for updates and support. Modern applications can improve staff efficiency, reduce maintenance expenses, and lead to better utilization of resources for strategic initiatives that deliver greater value to the business.

Easier Integration

Application modernization supports integration with technologies and architectural best practices that enhance interoperability, flexibility, and efficiency. Using technologies such as microservices, APIs, containers, standardized protocols, and/or cloud services, it’s easier to integrate modernized applications within complex IT environments.

Support for Innovation

Legacy applications often make it difficult to incorporate newer technologies, hindering innovation. Modernizing applications allows organizations the ability to leverage emerging technologies, such as machine learning and Internet of Things (IoT) for competitive advantage.

Database Application Modernization with Ingres NeXT

In summary, database application modernization is a strategic digital transformation initiative that can help organizations stay ahead in the digital age.  However, application modernization can be expensive and risky without the right approach.

Ingres NeXt is designed to protect existing database application investments in OpenROAD while leveraging them in new ways to add value to your business, without costly and lengthy rewrites. Flexible options to modernize your OpenROAD applications include:

  • ABF and Forms-Based Applications – Modernize ABF applications to OpenROAD frames using the abf2or migration utility and extend converted applications to mobile and web applications.
  • OpenROAD and Workbench IDE – Migrate partitioned ABF applications to OpenROAD frames.
  • OpenROAD Server – Deploy applications securely in the OpenROAD Server to retain and use application business logic.

In addition, The Ingres NeXt Readiness Assessment offers a pre-defined set of professional services that can lower your risk for application modernization and increase your confidence for a successful cloud journey. The service is designed to assist you with understanding the requirements to modernize Ingres and ABF or OpenROAD applications and to impart recommendations important to your modernization strategy formulation, planning, and implementation.

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Author: Teresa Wingfield

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Aug 1 2023
Aeriz: Unlocking the Hidden Value of SaaS Data

Getting the full value of data in your software as a service (SaaS) systems can be tricky. That’s because you can’t easily access the data needed for operations, supply chains, customer experiences, or other essential business functions.

Yet easy data access is possible. For example, Aeriz, a distributor of aeroponically grown cannabis, was able to optimize its supply chain by streamlining inventory management in the cloud. The company migrated and enriched data from an on-premises application to a modern cloud data platform.

As highlighted in the recent webinar, Unlocking the Hidden Value of SaaS Data to Support Operational Growth, breaking down barriers to data accessibility helped Aeriz reduce data preparation by 50%. The company collects and integrates a wide variety of data types to inform business decisions.

The ecosystem Aeriz had in place created several challenges, including relying on time-consuming processes to bring together and format data, which resulted in a time delay for insights. The company needed information in real time for decision making.

“If I’m looking at a 30-day or even a two-day time delay, I can’t tell if some of that data has problems with it if it’s not real time,” points out Joe Jones, Chief Information Officer for Aeriz.

Gaining the Ability to Analyze Complete Inventory Data

Aeriz, like many other organizations, needs accurate, trustworthy reports that give insights into the business. The reports must meet a variety of business needs, be consistent, and deliver the information employees in different parts of the organization need to drive their daily activities.

Time delays or inconsistent data that isn’t trustworthy limits insights. In turn, this creates barriers to stakeholders and others making the most informed decisions in a timely manner.

By implementing the Actian Data Platform, Aeriz is now able to get the reports, insights, and data capabilities it needs, at scale and when they’re needed. Aeriz can analyze all of its inventory data, enrich the information with data from other sources such as the general ledger and Salesforce, and deliver accurate and timely reports. This gives Aeriz the ability to optimize its entire supply chain, use advanced systems for aeroponic cultivation processes, and solve business challenges.

The Actian platform allows Aeriz to easily bring together disparate data sets on a single platform for analysis, then move the data, if needed, to other systems dedicated to the supply chain, financials, or other business areas. Actian improves efficiencies across three main areas for Aeriz:

  1. Data access and ease of use
  2. Complete and timely data insights
  3. Reduced time and resources spent on tasks

“If you’re looking at this from a non-technical standpoint, the end result is we got the data that we wanted quickly, and it’s meaningful,” Jones says. “It’s getting the important data information into the appropriate hands as quickly as possible and making sure it’s correct.”

Making Data Analytics Easy

Organizations across all verticals face many of the same challenges as Aeriz. They experience difficulties extracting data from legacy SaaS systems and applications, and many also lack the skills needed to effectively analyze the data.

Actian has been managing the world’s most critical data for customers for more than 50 years—Actian was in the room when data happened. Actian offers an innovative data platform that makes it easy for users to connect, manage, and analyze data without requiring advanced skills or IT intervention.

Watch the webinar co-hosted by Actian and Aeriz to find out why Aeriz chose Actian after looking at multiple vendors. Also, find out how the platform offers visibility and accuracy to make intelligent decisions quickly, enables companies like Aeriz to get data out of SaaS systems for real-time insights, and provides performance information on supply chains and an entire product lifecycle.

Watch the Webinar

Related resources you may find useful:

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Author: Jennifer Jackson

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Jul 24 2023
De-Risking The Road to Cloud: 6 Questions to Ask Along the Way

In my career, I’ve had first-hand experience as both a user and a chooser of data analytics technology, and have also had the chance to talk with countless customers about their data analytics journey to the cloud. With some reflection, I’ve distilled the learnings down to 6 key questions that every technology and business leader should ask themselves to avoid pitfalls along the way to the cloud so they can achieve its full promise.

1. What is my use case?

Identifying your starting point is the critical first step of any cloud migration. The most successful cloud migrations within our customer base are associated with a specific use case. This focused approach puts boundaries around the migration, articulates the desired output, and enables you to know what success looks like. Once a single use case has been migrated to the cloud, the next one is easier and often relies on data that has already been moved.

2. How will we scale over time?

Once you’ve identified the use case, you’ll need to determine what scaling looks like for your company. The beauty of the cloud is that it’s limitless in its scalability; however, businesses do have limits. Without planning for scale, businesses run the risk of exceeding resources and timelines.

To scale quickly and maximize value, I always recommend customers evaluate use cases based on level of effort and business value: plotting each use case in a 2Ă—2 matrix will help you identify the low effort, high value areas to focus on. By planning ahead for scale, you de-risk the move to the cloud because you understand what lies ahead.

3. What moves, what doesn’t, and what’s the cost of not planning for a hybrid multi-cloud implementation?

We hear from our customers, especially those in Europe, that there is a need to be deliberate and methodical in selecting the data that moves to the cloud. Despite the availability of data masking, encryption, and other protective measures available, concerns about GDPR and privacy are still very real. These factors need to be considered as the cloud migration roadmap is developed.

Multi-cloud architectures create resiliency, address regulatory requirements, and help avoid the risk of vendor lock-in. The benefits of multi-cloud environments were emphasized in a recent meeting with one of our EMEA-based retail customers. They experienced significant lost revenue and reputation damage after an outage of one of the largest global cloud service providers. The severe impact of this singular outage made them rethink a single cloud strategy and move to multi-cloud as part of their recovery plan.

4. How do I control costs?

In our research on customers’ move to the cloud, we found that half of organizations today are demanding better cost transparency, visibility, and planning capabilities. Businesses want a simple interface or console to determine which workloads are running and which need to be stopped – the easier this is to see and control, the better. Beyond visibility in the control console, our customers also use features such as idle stop, idle sleep, auto-scaling, and warehouse scheduling to manage costs. Every company should evaluate product performance and features carefully to drive the best cost model for the business. In fact, we’ve seen our health insurance customers leverage performance to control costs and increase revenue.

5. What skills gaps will I need to plan for, and how will I address them?

Our customers are battling skills gaps in key areas, including cloud, data engineering, and data science. Fifty percent of organizations lack the cloud skills to migrate effectively to the cloud, and 45 percent of organizations struggle with data integration capacity and challenges, according to our research. Instead of upskilling a team, which can often be a slow and painful process, lean on the technology and take advantage of as-a-service offerings. We’ve seen customers that engage in services agreements take advantage of platform co-management arrangements, fully managed platform services, and outsourcing to help offset skills gap challenges.

6. How will I measure success?

Look beyond cost and measure success based on the performance for the business. Ask yourself: is your cloud solution solving the problem you set out to solve? One of our customers, Met Eireann, the meteorological service for Ireland, determined that query speed was a critical KPI to measure. They found after moving to the cloud that performance improved 60-600 times and reduced query result time down to less than a second. Every customer measures success differently, whether it’s operational KPIs, customer experience, or data monetization. But whatever the measure, make sure you define success early and measure it often.

Making the move to the cloud is a journey, not a single step. Following a deliberate path, guided by these key questions, can help you maximize the value of cloud, while minimizing risk and disruption. With the right technology partner and planning, you can pave a smooth road to the cloud for your organization and realize true business value from your data.

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Author: Jennifer Jackson

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May 4 2023
How Your Peers are Experiencing their Journeys to the Cloud

According to new customer research from Actian, “Data Analytics Journey to the Cloud,” over 70% of companies are mandating that all new data analytics applications must use cloud-based platforms. Our research reveals many good reasons why the rush to the cloud is on. It also shows that organizations can run into cloud migration roadblocks, that prevent them from realizing the full potential of running their data analytics in the cloud.

Read our eBook to get insights from 450 business and technical leaders across industries and company sizes to improve your chances of a smoother cloud journey. Here are a few highlights of what these leaders shared on their cloud migration:

  • Over 60% of companies measure the impact of data analytics on their business.
  • Data privacy is the top challenge facing companies transitioning to the cloud.
  • More than half of companies say that scaling their business growth is a major challenge and are using cloud-based data analytics to address this.
  • Customer 360 customer analytics is the leading use case for companies.
  • Over 50% of companies are using cloud-based analytics to measure and improve customer experience key performance indicators (KPIs).
  • More than half of companies use data analytics to address their talent challenges.
  • Over 50% of companies use cloud-based data analytics to impact their employee experience and talent management KPIs.

Making your Cloud Migration Easier

Our research provides additional details that can help you become more confident in your cloud migration, improve planning, and better leverage cloud resources by understanding how other organizations approach their migration. If you’re already in a cloud, multi-cloud, or hybrid environment, you can use insights in our eBook to modernize applications, business processes, and data analytics in the cloud.

Register for our eBook to find out more about:

  • Leading Drivers of Cloud Transitions
  • Data Analytics Challenges and Cloud Migration Friction Points
  • Top Cloud-Native Technologies in Operation
  • Most Common Real-World Analytics Use Cases
  • How to Deliver New Capabilities.

You might also want to sign up for a free trial of the Avalanche Cloud Data Platform. You’ll discover how this modern platform simplifies how you connect, manage, and analyze your data.

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Author: Teresa Wingfield

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Apr 27 2023
Using Cloud Data Analytics to Drive Engagement

The decisions a business makes to help drive revenue and increase customer loyalty are only as good as the available data being referenced. Given the state of consumer demands and the changing ways they prefer to interact with brands, now is a crucial time for businesses to take stock of their cloud data analytics strategies. If data in the cloud isn’t being effectively integrated into the enterprise for analysis and insights, then meaningful business decisions cannot be made accurately. 

Customers are now taking their buying experiences more seriously than ever before. Nearly three-quarters of US consumers rank their experience dealing with a business as being important to their buying decisions. A large majority (86%) say they’d even pay more if it meant getting a better customer experience (CX) out of it. 

For businesses, this means that learning as much as possible about customers and getting their buying experience right is the #1 priority. Combining the power of modern-day analytics with the flexibility offered by the cloud can help businesses generate the real-time insights needed to grow and develop CX. Understanding a customer through data requires a thoughtful approach to cloud data analytics and how to effectively harness data for maximum output.  

Cloud Data Analytics, Explained 

The phrase “cloud data analytics” can mean many things to many different businesses, but broadly speaking, it’s all about using data to make smarter decisions to retain customers and win new ones. In some cases, it may refer to the way customer information is gathered to profile a new target sector. In other cases, it may be referring to the way a business pinpoints where a customer is on their customer lifecycle and the ways in which they’ve engaged with a brand. 

However, the goal of cloud data analytics is to paint a holistic image of how to best reach the audiences that are needed to push the business forward. The use and application of these analytics has surged within the past few years. The rise of social media in the past decade has created groundswells of data on consumer feedback, with sites like Facebook and Instagram providing spaces for customers to describe their experiences with brands. Similarly, aggregator sites like G2 Crowd and Quora allow for reviews and direct questions to be asked to and about companies. 

Businesses can leverage this data for their analytics in several ways, but perhaps the most important gain is using those insights to improve marketing and advertising campaigns. Consumers want personalization more than ever when interacting with businesses, and the insights generated from existing customer data can help make that personalization a reality.  

Understanding a consumer’s buying history and behavior can better help marketers choose the messaging that will resonate best with that customer and hopefully retain them. The need for personalization here cannot be overstated – competitive businesses must know their customers.  

I’m sure that we’ve all gotten offers from companies after visiting their website or buying a product. If a consumer buys a set of sheets online from a major retailer, the next email they receive should probably be for a sale on comforters, not refrigerators. Too many irrelevant offers, and your customers will begin to view little value in your communications and unsubscribe, meaning losing opportunities to attain leads. 

Cloud data analytics can also help organizations meet consumers where they are and on the channels they prefer. As mentioned, the near-ubiquitous use of social media in recent years has ushered in a new wave of opportunities for marketers to meet consumers on these platforms. Leveraging data in the cloud for analytics can help organizations build up an effective social media strategy, one that offers insights into the way customers are using these platforms. Given the nature of today’s interconnected world, social media represents a huge chance for marketers to meet their customers on familiar ground. 

Moving up to the Cloud 

Before a cloud data analytics strategy can get off the ground, the data being used needs to be clean, secure and easily accessible in infrastructure that can scale with today’s data growth. Traditional storage setups like on-premises data warehouses may have a role in today’s enterprise tech stack, but they can’t keep pace with the explosive growth of data from marketing applications. This means businesses still using legacy data centers should consider a move to the cloud for data storage.  

By leveraging a cloud storage model, users can dynamically scale their warehouses according to their business needs. Cloud data warehouses also ensure that the datasets stored inside of them are structured, compliant with regulatory standards, accurate, and accessible to any team that needs access. Furthermore, cloud-based warehouse architectures are significantly speedier than their on-premises counterparts, so you gain access to customer data quickly and efficiently – allowing you to meet customer demands as they happen. 

Perhaps most important, by leveraging the elasticity of the cloud, you have a more cost-effective way to handle spikes in business activity. Seasonality, market changes, and changes in current events can be addressed immediately, instead of wasting time waiting on infrastructure provisioning to accommodate the change in demand. This is particularly true when that demand is unforeseen, like we witnessed during the early days of the pandemic. 

Putting it All to Use 

Now that the goals of a customer data analytics strategy have been identified and the data has been moved to the cloud, a business can then begin using the data for analysis. Here are some key ways to leverage data to connect with customers: 

Find Areas of Opportunity 

It’s important to know your customers as intimately as possible, including their likes, dislikes and needs. The more you know about your customer base, the better you can pinpoint areas of opportunity within your company. The more opportunities you find, the higher chance you have of meeting those needs and making a sale. 

Keep an Eye on Customer Sentiment 

There are more channels than ever for customers to leave product reviews, ask questions, and engage in conversations surrounding your products. A large portion of those channels will not be within your control, but by leveraging the data from these places, you can not only respond to customers where they are, but over time gain a bird’s eye view of customer sentiment as well – both good and bad. The trends you uncover will help your product teams to address areas of improvement and help your marketing teams to zero in on clear value propositions. 

Get Early Warning Signs Before They Happen 

One of the most important benefits of customer data analytics is being able to see early warning signs before shifts in behavior happen. Whether that means a dip in sales or a shift in sentiment from customers, getting ahead of changes can give you more time to react and address issues before they impact your goals. Being able to take preemptive action will allow you to do some damage control before it becomes an irreversible issue for your company. Effectively leveraging cloud data analytics can be a major influence on how businesses drive CX and secure revenue. Access to clean data that can be easily shared can unlock new insights on customers and how to keep them coming back for more. 

For more information on how the Avalanche Cloud Data platform can help you better connect your cloud data for real-time analytics, check out our blog. 

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Author: Traci Curran

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Apr 19 2023
Steffen Kläbe Wins Best Paper at 2023 EDBT/ICDT Conference

We’d like to recognize Steffen Kläbe, a Research Engineer at Actian in llmenau (Thuringia, Germany). He attended the 2023 joint conference by EDBT/ICDT in Greece, one of the top database conferences worldwide, where he presented two research papers. For his research on Patched Multi-Key Partitioning for Robust Query Performance he received an award for Best Paper. In the research community, this award is quite a success.

View the abstract: 

“Data partitioning is the key for parallel query processing in modern analytical database systems. Choosing the right partitioning key for a given dataset is a difficult task and crucial for query performance. Real world data warehouses contain a large amount of tables connected in complex schemes resulting in an overwhelming amount of partition key candidates. In this paper, we present the approach of patched multi-key partitioning, allowing to define multiple partition keys simultaneously without data replication. The key idea is to map the relational table partitioning problem to a graph partition problem in order to use existing graph partitioning algorithms to find connectivity components in the data and maintain exceptions (patches) to the partitioning separately. We show that patched multi-key partitioning offer opportunities for achieving robust query performance, i.e. reaching reasonably good performance for many queries instead of optimal performance for only a few queries.” 

Kläbe’s additional paper Exploration of Approaches for In-Database ML covers the increasing role of integrating ML models with specialized frameworks for classification or prediction. 

View the abstract: 

“Database systems are no longer used only for the storage of plain structured data and basic analyses. An increasing role is also played by the integration of ML models, e.g., neural networks with specialized frameworks, and their use for classification or prediction. However, using such models on data stored in a database system might require downloading the data and performing the computations outside. In this paper, we evaluate approaches for integrating the ML inference step as a special query operator – the ModelJoin. We explore several options for this integration on different abstraction levels: relational representation of the models as well as SQL queries for inference, the use of UDFs, the use of APIs to existing ML runtimes and a native implementation of the ModelJoin as a query operator supporting both CPU and GPU execution. Our evaluation results show that integrating ML runtimes over APIs perform similarly to a native operator while being generic to support arbitrary model types. The solution of relational representation and SQL queries is most portable and works well for smaller inputs without any changes needed in the database engine.”

Congratulations, Steffan! We look forward to seeing more of your wins and research in the future. 

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Author: Saquondria Burris

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