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Feb 27 2024
The Link Between Trusted Data and Expanded Innovation

One highlight of my job is being able to talk to customers and prospective customers throughout the year at various events. What I keep hearing is that data is hard, and this holds true for companies of all sizes. And they’re right. Data can be hard. It can be hard to integrate, manage, govern, secure, and analyze. Building pipelines to new data sources can also be hard.

Business and IT both need data to be accessible to all users and applications, cost-effective to store, and deliver real-time insights. Any data challenges will limit these capabilities and present major barriers to innovation. That’s why we’ve made it our mission to make data easy and trustworthy.

Actian exists to provide the most trusted, flexible, and easy-to-use data platform on the market. We know that’s a bold promise and requires solving a lot of your data pain points. Yet we also know that to be truly data driven, you must have uninterrupted access to trusted data.

Overcoming the Trust Barrier

At Actian, we’ve been saying for a long time that you need to be able to trust your data. For too many companies, that’s not happening or it’s not happening in a timely manner. For example, nearly half—48%—of CEOs worry about data accuracy, according to IBM, while Gartner found that less than half of data and analytics teams—just 44%—are effectively providing value to their organization.

These numbers are unacceptable, especially in the age of technology. Everyone who uses data should be able to trust it to deliver ongoing value. So, we have to pause and ask ourselves why this isn’t happening. The answer is that common barriers often get in the way of reaching data goals, such as:

  • Silos that create isolated, outdated, and untrustworthy data.
  • Quality issues, such as incomplete, inaccurate, and inconsistent data.
  • Users do not have the skills needed to connect and analyze data, so they rely on IT.
  • Latency issues prevent real-time data access, which limits timely insights.
  • Data management problems that existed on-premises were migrated to the cloud.

Organizations know they have some or all of these problems, but they often don’t know what steps are needed to resolve them. Actian can help. We have the technology and expertise to enable data confidence—regardless of where you are on your data journey.

Innovation Starts with Trustworthy Data

What if you could swiftly go from data to decision with full confidence and ease? It doesn’t have to be a pipe dream. The solution is readily available now. It ensures you’re using high-quality, accurate data so you have full confidence in your decision-making. It simplifies data transformations, empowering you to get the data you want, when and how you want it, regardless of your skill level, and without relying on IT. Plus, you won’t have to wait for data because it gets delivered in real-time.

The Actian Data Platform makes data easy-to-use, allowing you to meet the needs of more business users, analysts, and data-intensive applications. You can collect, manage, and analyze data in real-time with our transactional database, data integration, data quality, and data warehouse capabilities working together in a single, easy-to-use platform.

The platform lets you manage data from any public cloud, multi- or hybrid cloud, and on-premises environment through a single pane of glass. The platform’s self-service data integration lowers costs while enabling you to perform more use cases without needing multiple data products.

What does all of this mean for your business? It means that data integration, access, and quality are easier than ever. It also means that you can trust your data to make confident decisions that accelerate your organization’s growth, foster new levels of innovation, support your digital transformation, and deliver other business value.

Enabling a Data-Driven Culture

With data volumes becoming more robust, having immediate access to high-quality data is essential, but challenging. Any problems with quality, latency, or integration will compound as data volumes grow, leading to potentially misinformed decision-making and mistrust in the data. Establishing data quality standards, making integration and access easy, and putting data in the hands of everyone who needs it advances the business, promotes a data-driven culture, and drives innovation. And this is where Actian can play a critical role.

What makes the Actian Data Platform unique, at a high level, is its ability to consolidate various data functions into a single platform, making data readily available and easy to use across your organization.

The platform handles extract, transform, and load (ETL), data transformation, data quality checks, and data analytics all in one place. Bringing everything and everyone together on a single platform lowers costs and reduces the resources needed to manage your data system. You benefit from real-time, trustworthy data across the entire organization, giving you full confidence in your data.

When you trust your data, you have the ability—and the confidence—to explore more use cases, increase revenues, reduce costs, fast-track innovation, win market share, and more for a strategic edge in your industry. Our customers are using data to drive new successes everyday!

Related resources you may find useful:

Top Capabilities to Look for in Database Management Tools

The Actian Data Platform’s Superior Price-Performance

How to Build an Effective Data Management Project Plan

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Author: Actian Corporation

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Feb 15 2024
How to Optimize Data In Any Environment

New demands, supply chain complexity, truly understanding customers, and other challenges have upended the traditional business landscape and forced organizations to rethink their strategies and how they’re using data. Organizations that are truly data-driven have opportunities to gain new market share and grow their competitive advantage. Those that don’t will continue to struggle—and in a worst-case scenario, may not be able to keep their doors open.

Data Is Needed to Drive and Support Use Cases

As organizations face the threat of a recession, geopolitical instability, concerns about inflation, and uncertainty about the economy, they look to data for answers. Data has emerged as a critical asset for any organization striving to intelligently grow their business, avoid costly problems, and position themselves for the future.

As explained in the webinar “Using Data in a Downturn: Building Business Resiliency with Analytics,” successful organizations optimize their data to be proactive in changing markets. The webinar, featuring William McKnight from McKnight Consulting Group, notes that data is needed for a vast range of business uses, such as:

  • Gaining a competitive advantage
  • Increasing market share
  • Developing new products and services
  • Entering new markets
  • Increasing brand recognition and customer loyalty
  • Improving efficiency
  • Enhancing customer service
  • Developing new technologies

McKnight says that when it comes to prioritizing data efforts, you should focus on projects that are easy to do with your current technology set and skill set, those that align with your business priorities, and ones that offer a high return on investment (ROI).

Justifying Data and Analytics Projects During a Downturn

The webinar explains why data and analytics projects are needed during an economic downturn. “Trusted knowledge of an accurate future is undoubtedly the most useful knowledge to have,” McKnight points out. Data and analytics predict that future, giving you the ability to position your company for what’s ahead.

Economic conditions and industry trends can change quickly, which means you need trustworthy data to inform the analytics. When this happens, you can uncover emerging opportunities such as products or features your customers will want or identify areas of risk with enough time to take action.

McKnight explains in the webinar that a higher degree of accuracy in determining your future can have a significant impact on your bottom line. “If you know what’s going to happen, you can either like it and leave it, or you can say, ‘I don’t like that, and here’s what I need to do to tune it,’ and that’s the essence of analytics,” he says.

Applying Data and Analytics to Achieve High-Value Results

Not surprisingly, the more data you make available for analytics, the more precise your analytics will be. As the webinar explains, artificial intelligence (AI) can help with insights. AI enhances analytics, provided the AI has the robust and quality data sets needed to deliver accurate and actionable results. The right approach to data and analytics can help you determine the next best step you can take for your business.

You can also use the insights to drive business value, such as creating loyal customers and repeat buyers, and proactively adjusting your supply chain to stay ahead of changing conditions. McKnight says in the webinar that leading companies are using data and customer analytics to drive ROI in a myriad of ways, such as optimizing:

  • Product placement in stores
  • Product recommendations
  • Content recommendations
  • Product design and offerings
  • Menu items in restaurants

All of these efforts increase sales. Likewise, using data and analytics can drive results across the supply chain. For example, you can use data to optimize inventory and ensure fast delivery times, or incorporate real-time data on customer demand, inventory levels, and transportation logistics to have products when and where they’re needed. Similarly, you can take a data-driven approach to demand forecasting, then optimize product distribution, and improve visibility across the entire supplier network.

Data Best Practices Hold True in Soft Economies

Using data to drive the business and inform decision-making is essential in any economy. During an economic downturn, you may need to shift priorities and decide what projects and initiatives to pursue, and which to pause or discontinue.

To help with these decisions, you can use your data foundation, follow data management best practices, continue to use data virtualization, and ensure you have the ability to access accurate data in real time. A modern data platform is also needed to integrate and leverage all your data.

The Actian Data Platform offers integration as a service, makes data easy to use, gives users confidence in their data, improves data quality, and more. The platform empowers you to go from data source to decision with confidence. You have the ability to better utilize data in an economic downturn, or any other market conditions.

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Jan 16 2024
How Engineers Can Improve Database Reliability

Database reliability is broadly defined as a database that performs consistently and correctly, without interruptions or failures, to ensure accurate and consistent data is readily available for all users. As your organization becomes increasingly data-driven and realizes the importance of using data for decision-making, stakeholders must be able to trust your data. Building trust and having confidence requires complete, accurate, and easily accessible data, which in turn requires a reliable database.

For data to be considered reliable, it should be timely, accurate, consistent, and recoverable. Yet as data processes become more complex, data sources expand, data volumes grow, and data errors have a more significant impact, more attention is given to data quality. It’s also why the role of the database reliability engineer (DBRE) becomes more important.

Preventing data loss and delivering uninterrupted data are increasingly important for modern businesses. Today’s data users expect to be able to access data at any time, from virtually any location. If that doesn’t happen, analysts and other business users lose trust in the database—and database downtime can be extremely expensive. Some estimates put the cost of downtime at approximately $9,000 per minute, with some large organizations losing hundreds of thousands of dollars per hour.

Enable a Highly Functioning and Reliable Database

It’s best to think of a DBRE as an enabler. That’s because the database reliability engineer enables a resilient, scalable, and functional database to meet the demands of users and data-intensive applications. Engineers can ensure database reliability by following a strategy that includes these essential components and capabilities:

  • Optimize database performance. Use tuning tools to gain maximum performance for fast, efficient processing of queries and transactions. Following best practices to optimize performance for your particular database keeps applications running correctly, provides good user experiences, uses resources effectively, and scales more efficiently.
  • Provide fault tolerance. Keep the database operating properly even when components fail. This ensures data is always available to enable business continuity. In addition to offering high availability, fault tolerance delivers uninterrupted database services while assisting with disaster recovery and data integrity. For some industries, fault tolerance may be needed to meet regulatory compliance requirements.
  • Replicate data. Create and manage multiple copies of data in different locations or on different servers. Data replication ensures a reliable copy of data is available if another copy becomes damaged or inaccessible due to a failure—organizations can switch to the secondary or standby server to access the data. This offers high availability by making sure a single point of failure does not prevent data accessibility.
  • Have a backup and restore strategy. Back up data regularly and store it in a secure location so you can quickly recover it if data is lost or corrupted. The data backup process can be automated, and the restoration process must be tested to ensure it works flawlessly when needed. Your backup and restore strategy is critical for protecting valuable data, meeting compliance regulations in some industries, and mitigating the risk of lost data, among other benefits.
  • Keep data secure. Make sure data is safe from breaches and unauthorized access, while making it readily available to anyone across the organization who needs it. Well-established database security protocols and access controls contribute to keeping data safe from internal and external threats.
  • Balance workloads. Implement a load-balancing strategy to improve query throughput speed for faster response times, while also preventing a single server from becoming overloaded. Load balancing distributes workloads across multiple database services, which minimizes latency and better utilizes resources to handle more workloads faster.

Improve and Monitor Your Database

Once you have the technologies, processes, and strategy in place for a reliable database, the next step is to keep it running like a finely tuned machine. These approaches help sustain database reliability:

  • Use database metrics. Determine what database reliability looks like for your organization, then identify the metrics needed to ensure you’re meeting your baseline. You can implement database alerts to notify database administrators of issues, such as performance falling below an established metric. Having insights into metrics, including resource utilization and query response speed, allows you to make informed decisions about scaling, capacity planning, and resource allocation.
  • Monitor the database. Track the database’s performance and usage to uncover any issues and to ensure it meets your performance goals. Monitoring efforts also help you proactively identify and prevent problems that could slow down the database or cause unexpected downtime.
  • Continually use optimization techniques. Performance tuning, data partitioning, index optimization, caching, and other tasks work together to achieve a highly optimized database. Performing regular maintenance can also prevent issues that negatively impact the database. Consider database optimization a critical and ongoing process to maintain a responsive and reliable database.
  • Establish data quality standards. Quality data is a must-have, which requires data that is timely, integrated, accurate, and consistent. Data quality tools and a data management strategy help maintain data quality to meet your compliance needs and usability standards.

Reliable Databases to Meet Your Business and IT Needs

Taking an engineering approach to improve database reliability gives you the data quality, availability, and performance needed to become a truly data-driven organization. A high-functioning, easy-to-use database encourages data integration to eliminate data silos and offer a single source of truth.

Actian offers a range of modern databases to meet your specific business and IT needs. These databases enable you to make confident, data-driven decisions that accelerate your organization’s growth. For example:

  • Actian Ingres offers powerful and scalable transactional processing capabilities.
  • Zen databases are a family of low-maintenance, high performance, and small footprint databases.
  • NoSQL has high-availability, replication, and agile development capabilities, and makes application development fast and easy.
  • OneDB gives you a fast, affordable path to the cloud with minimal risk.

We also have the Actian Data Platform, which is unique in its ability to collect, manage, and analyze data in real-time, with its transactional database, data integration, data quality, and data warehouse capabilities in an easy-to-use platform.

Related resources you may find useful:

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Jan 2 2024
Top Capabilities to Look for in Database Management Tools

As businesses continue to tap into ever-expanding data sources and integrate growing volumes of data, they need a solid data management strategy that keeps pace with their needs. Similarly, they need database management tools that meet their current and emerging data requirements.

The various tools can serve different user groups, including database administrators (DBAs), business users, data analysts, and data scientists. They can serve a range of uses too, such as allowing organizations to integrate, store, and use their data, while following governance policies and best practices. The tools can be grouped into categories based on their role, capabilities, or proprietary status.

For example, one category is open-source tools, such as PostgreSQL or pgAdmin. Another category is tools that manage an SQL infrastructure, such as Microsoft’s SQL Server Management Studio, while another is tools that manage extract, transform, and load (ETL) and extract, load, and transform (ELT) processes, such as those natively available from Actian.

Using a broad description, database management tools can ultimately include any tool that touches the data. This covers any tool that moves, ingests, or transforms data, or performs business intelligence or data analytics.

Data Management Tools for Modern Use Cases

Today’s data users require tools that meet a variety of needs. Some of the more common needs that are foundational to optimizing data and necessitate modern capabilities include:

  • Data management: This administrative and governance process allows you to acquire, validate, store, protect, and process data.
  • Data integration: Integration is the strategic practice of bringing together internal and external data from disparate sources into a unified platform.
  • Data migration: This entails moving data from its current or storage location to a new location, such as moving data between apps or from on-premises to the cloud.
  • Data transformation: Transformative processes change data from one format or structure into another for usage and ensure it’s cleansed, validated, and properly formatted.
  • Data modeling: Modeling encompasses creating conceptual, logical, and physical representations of data to ensure coherence, integrity, and efficiency in data management and utilization.
  • Data governance: Effective governance covers the policies, processes, and roles used to ensure data security, integrity, quality, and availability in a controlled, responsible way.
  • Data replication: Replicating data is the process of creating and storing multiple copies of data to ensure availability and protect the database against failures.
  • Data visualization: Visualizing data turns it into patterns and visual stories to show insights quickly and make them easily understandable.
  • Data analytics and business intelligence: These are the comprehensive and sophisticated processes that turn data into actionable insights.

It’s important to realize that needs can change over time as business priorities, data usage, and technologies evolve. That means a cutting-edge tool from 2020, for example, that offered new capabilities and reduced time to value may already be outdated by 2024. When using an existing tool, it’s important to implement new versions and upgrades as they become available.

You also want to ensure you continue to see a strong return on investment in your tools. If you’re not, it may make more sense from a productivity and cost perspective to switch to a new tool that better meets your needs.

Ease-of-Use and Integration Are Key

The mark of a good database management tool—and a good data platform—is the ability to ensure data is easy-to-use and readily accessible to everyone in the organization who needs it. Tools that make data processes, including analytics and business intelligence, more ubiquitous offer a much-needed benefit to data-driven organizations that want to encourage data usage for everyone, regardless of their skill level.

All database management tools should enable a broad set of users—allowing them to utilize data without relying on IT help. Another consideration is how well a tool integrates with your existing database, data platform, or data analytics ecosystem.

Many database management tool vendors and independent software vendors (ISVs) may have 20 to 30 developers and engineers on staff. These companies may provide only a single tool. Granted, that tool is probably very good at what it does, with the vendor offering professional services and various features for it. The downside is that the tool is not natively part of a data platform or larger data ecosystem, so integration is a must.

By contrast, tools that are provided by the database or platform vendor ensure seamless integration and streamline the number of vendors that are being used. You also want to use tools from vendors that regularly offer updates and new releases to deliver new or enhanced capabilities.

If you have a single data platform that offers the tools and interfaces you need, you can mitigate the potential friction that oftentimes exists when several different vendor technologies are brought together, but don’t easily integrate or share data. There’s also the danger of a small company going out of business and being unable to provide ongoing support, which is why using tools from large, established vendors can be a plus.

Expanding Data Management Use Cases

The goal of database management tools is to solve data problems and simplify data management, ideally with high performance and at a favorable cost. Some database management tools can perform several tasks by offering multiple capabilities, such as enabling data integration and data quality. Other tools have a single function.

Tools that can serve multiple use cases have an advantage over those that don’t, but that’s not the entire story. A tool that can perform a job faster than others, automate processes, and eliminate steps in a job that previously required manual intervention or IT help offers a clear advantage, even if it only handles a single use case. Stakeholders have to decide if the cost, performance, and usability of a single-purpose tool delivers a value that makes it a better choice than a multi-purpose tool.

Business users and data analysts often prefer the tools they’re familiar with and are sometimes reluctant to change, especially if there’s a long learning curve. Switching tools is a big decision that involves both cost and learning how to optimize the tool.

If you put yourself in the shoes of a chief data officer, you want to make sure the tool delivers strong value, integrates into and expands the current environment, meets the needs of internal users, and offers a compelling reason to make a change. You also should put yourself in the shoes of DBAs—does the tool help them do their job better and faster?

Delivering Data and Analytics Capabilities for Today’s Users

Tool choices can be influenced by no-code, low-code, and pro-code environments. For example, some data leaders may choose no- or low-code tools because they have small teams that don’t have the time or skill set needed to work with pro-code tools. Others may prefer the customization and flexibility options offered by pro-code tools.

A benefit of using the Actian Data Platform is that we offer database management tools to meet the needs of all types of users at all skill levels. We make it easy to integrate tools and access data. The Actian Platform offers no-code, low-code, and pro-code integration and transformation options. Plus, the unified platform’s native integration capabilities and data quality services feature a robust set of tools essential for data management and data preparation.

Plus, Actian has a robust partner ecosystem to deliver extended value with additional products, tools, and technologies. This gives customers flexibility in choosing tools and capabilities because Actian is not a single product company. Instead, we offer products and services to meet a growing range of data and analytics use cases for modern organizations.

Experience the Actian Data Platform for yourself. Take a free 30-day trial.

Related resources you may find useful:

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Author: Derek Comingore

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Dec 27 2023
The Actian Data Platform’s Superior Price-Performance

When it comes to choosing a technology partner, price and performance should be top of mind. “Price-performance” refers to the measure of how efficiently a database management system (DBMS) utilizes system resources, such as processing power, memory, and storage, in relation to its cost. It is a crucial factor for organizations to consider when selecting a DBMS, as it directly impacts the overall performance and cost-effectiveness of their data management operations. The Actian Data Platform can provide the price-performance you’re looking for and more.

Getting the most value out of any product or service has always been a key objective of any smart customer. This is especially true of those who lean on database management systems to help their businesses compete and grow in their respective markets, even more so when you consider the exponential growth in both data sources and use cases in any given industry or vertical. This might apply if you’re an insurance agency that needs real-time policy quote information, or if you’re in logistics and need the most accurate, up-to-date information about the location of certain shipments. Addressing use cases like these as cost-effectively as possible is key in today’s fast-moving world.

The Importance of Prioritizing Optimal Price-Performance

Today, CFOs and technical users alike are trying to find ways to get the best price-performance possible from their DBMS systems. Not only are CFOs interested in up-front acquisition and implementation costs, but also all costs downstream that are associated with the utilization and maintenance of whichever system they choose.

Technical users of various DBMS offerings are also looking for alternative ways to utilize their systems to save costs. In the back alleys of the internet (places like Reddit and other forums), users of various DBMS platforms are discussing how to effectively “game” their DBMS platforms to get the best price-performance possible, sometimes leading to the development of shadow database solutions just to try and save costs.

According to a December 2022 survey by Actian, 56% of businesses struggle to maintain costs as data volumes and workloads increase. These types of increases affect total cost of ownership and related infrastructure maintenance, support, query complexity, the number of concurrent users, and management overhead, which have a significant impact on the costs involved in using a database management system.

Superior Price-Performance

Having been established over 50 years ago, Actian was in the delivery room when enterprise data management was born. Since then, we’ve had our fingers on the pulse of the market’s requirements, developing various products that meet various use cases from various industries worldwide.

The latest version of the Actian Data Platform includes native data integrations with 300+ out-of-the-box connectors and scalable data warehousing and analytics that produce REAL real-time insights to more confident support decision-making. The Actian Data Platform can be used on-premises, in the cloud across multiple clouds, and in a hybrid model. The Actian Platform also provides no-code, low-code, and pro-code solutions to enable a multitude of users, both technical and non-technical.

The 2023 Gigaom TCP-H Benchmark Test

At Actian, we’re really curious about how our platform compared with other major players and whether or not it could help deliver the price-performance being sought after in the market. In June of 2023, we commissioned a TCP-H Benchmark test with GigaOm, pitting the Actian Data Platform against both Google Big Query and Snowflake. This test involved running 22 queries against a 30TB TCP-H data set. Actian’s response times were better than the competition in 20 of those 22 requests. Furthermore, the benchmark report revealed that:

  • In a test of five concurrent users, Actian was overall 3x faster than Snowflake and 9x faster than Big Query.

  • In terms of price-performance, the Actian Data Platform produced even greater advantages when running the five concurrent user TPC-H queries. Actian proved roughly 4x less expensive to operate than Snowflake, based on cost per query per hour, and 16x less costly than BigQuery.

These were compelling results. Overall, the GigaOm TCP-H benchmark shows that the Actian Data Platform is a high-performance cloud data warehouse that is well-suited for organizations that need to analyze large datasets quickly and cost-effectively.

Actian customer, the Automobile Association (AA), located in the United Kingdom, was able to reduce their quote response time to 400 milliseconds. Without the speed provided by the Actian Platform, they wouldn’t have been able to provide prospective customers the convenience of viewing insurance quotes on their various comparison pages, which allows them to gain and maintain a clear advantage over their competitors.

Let Actian Help

If price-performance is a key factor for you, and you’re looking for a complete data platform that will provide superior capabilities and ultimately lower your TCO, do these three things:

  1. Download a copy of the Gigaom TCP-H Benchmark report and read the results for yourself.
  2. Take the Actian Data Platform for a test-drive!
  3. Contact us! One of our friendly, knowledgeable representatives will be in touch with you to discuss the benefits of the Actian Data Platform and how we can help you have more confidence in your data-driven decisions that keep your business growing.

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Author: Phil Ostroff

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Dec 12 2023
Common Healthcare Data Management Issues … And How to Solve Them

A modern data management strategy treats data as a valuable business resource. That’s because data should be managed from creation to the point when it’s no longer needed in order to support and grow the business. Data management entails collecting, organizing, and securely storing data in a way that makes it easily accessible to everyone who needs it. As organizations create, ingest, and analyze more data than ever before, especially in the healthcare field, data management strategies are essential for getting the most value from data.

Making data management processes scalable is also critical, as data volumes and the number of data sources continue to rapidly increase. Unfortunately, many organizations struggle with data management problems, such as silos that result in outdated and untrustworthy data, legacy systems that can’t easily scale, and data integration and quality issues that create barriers to using data.

When these challenges enter the healthcare industry, the impact can be significant, immediate, and costly. That’s because data volumes in healthcare are enormous and growing at a fast rate. As a result, even minor issues with data management can become major problems as processes are scaled to handle massive data volumes.

Data management best practices are essential in healthcare to ensure compliance, enable data-driven outcomes, and handle data from a myriad of sources. The data can be connected, managed, and analyzed to improve patient outcomes and lower medical costs. Here are common data management issues in healthcare—and how to solve them:

Data Silos Are an Ongoing Problem

Healthcare data comes from a variety of sources, including patient healthcare records, medical notes and images, insurance companies, financial departments, operations, and more. Without proper data management processes in place, harnessing this data can get very complex, very fast.

Complexity often leads to data silos and shadow IT approaches. This happens when departments or individuals want to quickly access data, but don’t want to follow established protocols that could require IT help, so they take shortcuts. This results in islands of data that are not connected and may be outdated, inaccurate, or have other quality issues.

Breaking down silos and connecting data requires the right data platform. The platform should be scalable, have easy-to-use integration capabilities to unify data, and make data easy-to-access, without IT assistance. Making data easy discourages silos, fosters a data-driven culture that supports data management best practices, and allows all users to tap into the data they need.

Barriers to Data Integration and Quality

Many legacy systems used by healthcare organizations are not integration-friendly. They may have been built as a single-purpose solution and interoperability was not a primary concern. In today’s healthcare environment, connectivity is important to enable data sharing, automation, and visibility into the organization.

“The flow of data is as important as the flow of people,” according to FQHC Associates, which specializes in Federally Qualified Health Center (FQHC) programs. “One common issue in connected care is a lack of data standardization, in which the different platforms used by different departments are not mutually readable or easily transferable. This results in data silos, blocks productivity, and even worse, leads to misunderstandings or errors.”

Data integration—bringing together all required data from all available sources—on a single platform helps inform decision-making, delivers complete patient records, and enables healthcare data analytics. The Centers for Medicare & Medicaid Services (CMS) has mandates to prioritize interoperability—the ability for systems to “speak” to each other.

A modern platform is needed that offers simple integration and ensures data quality to give stakeholders confidence in their data. The platform must be able to integrate all needed data from anywhere, automate data profiling, and drive data quality for trusted results. Ensuring the accuracy, completeness, and consistency of healthcare data helps prevent problems, such as misdiagnosis or billing errors.

Complying with Ever-Changing Regulations

The healthcare industry is highly regulated, which requires data to be secure and meet compliance mandates. For example, patient data is sensitive and must meet regulations, such as the Health Insurance Portability and Accountability Act (HIPAA).

Non-compliance can result in stiff legal and financial penalties and loss of patient trust. Protecting patient data from breaches and unauthorized access is a constant concern, yet making data readily available to physicians when treating a patient is a must.

Regulations can be complex, vary by state, and continually evolve. This challenges healthcare organizations to ensure their data management plan is regularly updated to meet changing requirements. Implementing role-based access controls to view data, using HIPAA-compliant data management technologies, and encrypting data help with patient privacy and protection.

Similarly, data governance best practices can be used to establish clear governance policies. Best practices help ensure data is accurate, protected, and compliant. Healthcare organizations need a modern data platform capable of offering transparency into data processes to ensure they are compliant. Automating data management tasks removes the risk of human errors, while also accelerating processes.

Dealing with Duplicate Patient Records

The healthcare industry’s shift from paper-based patient records to electronic health records enabled organizations to modernize and benefit from a digital transformation. But this advancement came with a challenge—how to link a person’s data together in the same record. Too often, healthcare facilities have multiple records for the same patients due to name or address changes, errors when entering data, system migrations, healthcare mergers, or other reasons.

“One of the main challenges of healthcare data management is the complexity of managing and maintaining patient, consumer, and provider identities across the enterprise and beyond, especially as your organization grows organically and through partnerships and acquisition,” according to an article by MedCity News.

This problem increases data management complexity by having duplicate records for the same patients. Performing data cleansing can detect duplicate records and reconcile issues. Likewise, having a robust data quality management framework helps prevent the problem from occurring by establishing data processes and identifying tools that support data quality.

Delivering Trust in Healthcare Data

Many healthcare organizations struggle to optimize the full value of their data, due to a lack of data standards, poor data quality, data security issues, and ongoing delays in data delivery. All of these challenges reduce trust in data and create barriers to being a truly data-driven healthcare company.

Solving these issues and addressing common data management problems in healthcare requires a combination of technology solutions, data governance policies, and staff training. An easy-to-use data platform that solves issues for data scientists, managers, IT leaders, and others in healthcare organizations can help with data management, data visualization, and data accessibility.

For example, the Actian Data Platform gives users complete confidence in their data, improves data quality, and offers enhanced decision-making capabilities. It enables healthcare providers to:

  • Connect data sources. Integrate and transform data by building or using existing APIs via easy-to-use, drag-and-drop blocks for self-service, removing the need to use intricate programming or coding languages.
  • Connect to multiple applications. Create connections to applications offering a REST or SOAP API.
  • Broaden access to data. Use no-code, low-code, and pro-code integration and transformation options to broaden usability across the business.
  • Simplify data profiling. Profile data to identify data characteristics and anomalies, assess data quality, and determine data preparation needs for standardization.
  • Improve data quality.Track data quality over time and apply rules to existing integrations to quickly identify and isolate data inconsistencies.‌

Actian offers a modern integration solution that handles multiple integration types, allowing organizations to benefit from the explosion of new and emerging data sources and have the scalability to handle growing data volumes. In addition, the Actian Data Platform is easy to use, allowing stakeholders across the organizations to truly understand their data, ensure HIPAA compliance, and drive desired outcomes faster.

Find out how the platform manages data seamlessly and supports advanced use cases such as generative AI by automating time-consuming data preparation tasks. Try it for free.

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Nov 16 2023
Gen AI Best Practices for Data Scientists, Engineers, and IT Leaders

As organizations seek to capitalize on Generative AI (Gen AI) capabilities, data scientists, engineers, and IT leaders need to follow best practices and use the right data platform to deliver the most value and achieve desired outcomes. While many best practices are still evolving Gen AI is in its infancy.

Granted, with Gen AI, the amount of data you need to prepare may be incredibly large, but the same approach you’re now using to prep and integrate data for other use cases, such as advanced analytics or business applications, applies to GenAI. You want to ensure the data you gathered will meet your use case needs for quality, formatting, and completeness.

As TechTarget has correctly noted, “To effectively use Generative AI, businesses must have a good understanding of data management best practices related to data collection, cleansing, labeling, security, and governance.”

Building a Data Foundation for GenAI

Gen AI is a type of artificial intelligence that uses neural networks to uncover patterns and structures in data, and then produces content such as text, images, audio, and code. If you’ve interacted with a chatbot online that gives human-like responses to questions or used a program such as ChatGPT, then you’ve experienced Gen AI.

The potential impact of Gen AI is huge. Gartner sees it becoming a general-purpose technology with an impact similar to that of the steam engine, electricity, and the internet.

Like other use cases, Gen AI requires data—potentially lots and lots of data—and more. That “more” includes the ability to support different data formats in addition to managing and storing data in a way that makes it easily searchable. You’ll need a scalable platform capable of handling the massive data volumes typically associated with Gen AI.

Data Accuracy is a Must

Data preparation and data quality are essential for Gen AI, just like they are for data-driven business processes and analytics. As noted in eWeek, “The quality of your data outcomes with Generative AI technology is dependent on the quality of the data you use.

Managing data is already emerging as a challenge for Gen AI. According to McKinsey, 72% of organizations say managing data is a top challenge preventing them from scaling AI use cases. As McKinsey also notes, “If your data isn’t ready for Generative AI, your business isn’t ready for Generative AI.”

While Gen AI use cases differ from traditional analytics use cases in terms of desired outcomes and applications, they all share something in common—the need for data quality and modern integration capabilities. Gen AI requires accurate, trustworthy data to deliver results, which is no different from business intelligence (BI) or advanced analytics.

That means you need to ensure your data does not have missing elements, is properly structured, and has been cleansed. The prepped data can then be utilized for training and testing Gen AI models and gives you a good understanding of the relationships between all your data sets.

You may want to integrate external data with your in-house data for Gen AI projects. The unified data can be used to train models to query your data store for Gen AI applications. That’s why it’s important to use a modern data platform that offers scalability, can easily build pipelines to data sources, and offers integration and data quality capabilities.

Removing Barriers to Gen AI

What I’m hearing from our Actian partners is that organizations interested in implementing Gen AI use cases are leaning toward using natural language processing for queries. Instead of having to write in SQL to query their databases, organizations often prefer to use natural language. One benefit is that you can also use natural language for visualizing data. Likewise, you can utilize natural language for log monitoring and to perform other activities that previously required advanced skills or SQL programming capabilities.

Until recently, and even today in some cases, data scientists would create a lot of data pipelines to ingest data from current, new, and emerging sources. They would prep the data, create different views of their data, and analyze it for insights. Gen AI is different. It’s primarily about using natural language processing to train large language models in conjunction with your data.

Organizations still want to build pipelines, but with a platform like the Actian Data Platform, it doesn’t require a data scientist or advanced IT skills. Business analysts can create pipelines with little to no reliance on IT, making it easier than ever to pull together all the data needed for Gen AI.

With recent capability enhancements to our Actian Data Platform, we’ve enabled low code, no code, and pro code integration options. This makes the platform more applicable to engage more business users and perform more use cases, including those involving Gen AI. These integration options reduce the time spent on data prep, allowing data analysts and others to integrate and orchestrate data movement and pipelines to get the data they need quickly.

A best practice for any use case is to be able to access the required data, no matter where it’s located. For modern businesses, this means you need the ability to explore data across the cloud and on-premises, which requires a hybrid platform that connects and manages data from any environment, for any use case.

Expanding Our Product Roadmap for Gen AI

Our conversations with customers have revealed that they are excited about Gen AI and its potential solutions and capabilities, yet they’re not quite ready to implement Gen AI technologies. They’re focused on getting their data properly organized so it’ll be ready once they decide which use cases and Gen AI technologies are best suited for their business needs.

Customers are telling us that they want solid use cases that utilize the strength of Gen AI before moving forward with it. At Actian, we’re helping by collaborating with customers and partners to identify the right use cases and the most optimal solutions to enable companies to be successful. We’re also helping customers ensure they’re following best practices for data management so they will have the groundwork in place once they are ready to move forward.

In the meantime, we are encouraging customers to take advantage of the strengths of the Actian Data Platform, such as our enhanced capabilities for integration as a service, data quality, and support for database as a service. This gives customers the benefit of getting their data in good shape for AI uses and applications.

In addition, as we look at our product roadmap, we are adding Gen AI capabilities to our product portfolio. For example, we’re currently working to integrate our platform with TensorFlow, which is an open-source machine learning software platform that can complement Gen AI. We are also exploring how our data storage capabilities can be utilized alongside TensorFlow to ensure storage is optimized for Gen AI use cases.

Go From Trusted Data to Gen AI Use Cases

As we talk with customers, partners, and analysts, and participate in industry events, we’ve observed that organizations certainly want to learn more about Gen AI and understand its implications and applications. It’s now broadly accepted that AI and Gen AI are going to be critical for businesses. Even if the picture of exactly how Gen AI will be beneficial is still a bit hazy, the awareness and enthusiasm are real.

We’re excited to see the types of Gen AI applications that will emerge and the many use cases our customers will want to accomplish. Right now, organizations need to ensure they have a scalable data platform that can handle the required data volumes and have data management practices in place to ensure quality, trustworthy data to deliver desired outcomes.

The Actian Data Platform supports the rise of advanced use cases such as Generative AI by automating time-consuming data preparation tasks. You can dramatically cut time aggregating data, handling missing values, and standardizing data from various sources. The platform’s ability to enable AI-ready data gives you the confidence to train AI models effectively and explore new opportunities to meet your current and future needs.

The Actian Data Platform can give you complete confidence in your data for Gen AI projects. Try the platform for free for 30 days to see how easy data can be.

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Author: Vamshi Ramarapu

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Nov 13 2023
Introducing The Actian Data Platform: Redefining Speed and Price Performance

As the Vice President of Engineering at Actian, I have been very involved in the recent launch of our Actian Data Platform. My role in this major upgrade has been twofold—to ensure our easy-to-use platform offers rewarding user experiences, and to deliver the technology updates needed to meet our customers’ diverse data needs.  

On a personal level, I’m most excited about the fact that we put in place the building blocks to bring additional products onto this robust data platform. That means, over time, you can continue to seamlessly add new capabilities to meet your business and IT needs.  

This goes beyond traditional future-proofing. We have provided an ecosystem foundation for the entire Actian product suite, including products that are available now and those that will be available in the coming years. This allows you to bring the innovative Actian products you need onto our hybrid platform, giving you powerful data and analytics capabilities in the environment of your choice—in the cloud, on-premises, or both.   

Blazing Fast Performance at a Low Price Point 

One of the Actian Data Platform’s greatest strengths is its extreme performance. It performs query optimization and provides analytics at the best price performance when compared to other solutions. In fact, it offers a nine times faster speed advantage and 16 times cost savings over alternative platforms.  

This exceptional price performance, coupled with the platform’s ability to optimize resource usage, means you don’t have to choose between speed and cost savings. And regardless of which of our pricing plans you choose—a base option or enterprise-ready custom offering—you only pay for what you use.  

Our platform also offers other modern capabilities your business needs. For example, as a fully-managed cloud data platform, it provides data monitoring, security, backups, management, authentication, patching, usage tracking, alerts, and maintenance, freeing you to focus on your business rather than spending time handling data processes.   

Plus, the platform’s flexible and scalable architecture lets you integrate data from new and existing sources, then make the data available wherever you need it. By unifying data integration, data management, and analytics, the Actian Data Platform reduces complexity and costs while giving you fast, reliable insights. 

Easy-to-Use Offering for High-Quality Data and Integration 

Another goal we achieved with our platform is making it even simpler to use. The user experience is intuitive and friendly, making it easy to benefit from data access, data management, data analytics, and integrations. 

We also rolled out several important updates with our launch. One focuses on integration. For example, we are providing stronger integration for DataConnect and Link customers to make it easier than ever to optimize these platforms’ capabilities.  

We have also strengthened the integration and data capabilities that are available directly within the Actian Data Platform. In addition to using our pre-built connectors, you can now easily connect data and applications using REST- and SOAP-based APIs that can be configured with just a few clicks. To address data quality issues, the Actian Data Platform now provides the ability to create codeless transformations using a simple drag-and-drop canvas.  

The platform offers the best mix of integration, quality, and transformation tools. It’s one of the reasons why our integration as a service and data quality as a service are significant differentiators for our platform.  

With our data integration and data quality upgrades, along with other updates, we’ve made it easy for you to configure and manage integrations in a single, unified platform. Plus, with our native integration capabilities, you can connect to various data sources and bring that data into the data warehouse, which in turn feeds analytics. Actian makes it easy to build pipelines to new and emerging data sources so you can access all the data you need.  

Providing the Data Foundation for Generative AI 

We paid close attention to the feedback we received from customers, companies that experienced our free trial offer, and our partners about our platform. The feedback helped drive many of our updates, such as an improved user experience and making it easy to onboard onto the platform. 

I am a big proponent of quality being perceptive and tangible. With our updates, users will immediately realize that this is a high-quality, modern platform that can handle all of their data and data management needs. 

Many organizations are interested in optimizing AI and machine learning (ML) use cases, such as bringing generative AI into business processes. The Actian Data Platform lends itself well to these projects. The foundation for any AI and ML project, including generative AI, is to have confidence in your data. We meet that need by making data quality tooling natively available on our platform.  

We also have an early access program for databases as a service that’s been kickstarted with this platform. In addition, we’ve added scalability features such as auto-scaling. This enables your data warehouse to scale automatically to meet your needs, whether it’s for generative AI or any other project.  

Breaking New Ground in Data Platforms 

The Actian Data Platform monitors and drives the entire data journey, from integrations to data warehousing to real-time analytics. Our platform has several differentiators that can directly benefit your business:  

  • A unified data platform improves efficiency and productivity across the enterprise by streamlining workflows, automating tasks, and delivering insights at scale.  
  • Proven price performance reduces the total cost of ownership by utilizing fewer resources for compute activities—providing a more affordable solution without sacrificing performance—and can process large volumes of transactional data much faster than alternative solutions. 
  • Integration and data quality capabilities help mitigate data silos by making it easy to integrate data and share it with analysts and business users at all skill levels. You can cut data prep time to deliver business results quickly with secure integration of data from any source.  
  • REAL real-time insights meet the demand of analytics when speed matters. The platform achieves this with a columnar database enabling fast data loading, vectorized processing, multi-core parallelism, query execution in CPU cores/cache, and other capabilities that enable the world’s fastest analytics platform.  
  • Database as a service removes the need for infrastructure procurement, setup, management, and maintenance, with minimal database administration and cloud development expertise required, making it easy for more people to get more value from your data.  
  • Flexible deployment to optimize data using your choice of environment—public cloud, multi- or hybrid cloud, or on-premises—to eliminate vendor lock-in. You can choose the option that makes the most sense for your data and analytics needs.  

These capabilities make our platform more than a tool. More than a cloud-only data warehouse or transactional database. More than an integration platform as a service (iPaas). Our platform is a trusted, flexible, easy-to-use offering that gives you unmatched performance at a fraction of the cost of other platforms.  

How Can Easy-to-Use Data Benefit Your Business?  

Can you imagine how your business would benefit if everyone who needed data could easily access and use it—without relying on IT help? What if you could leverage your integrated data for more use cases? And quickly build pipelines to new and emerging data sources for more contextual insights, again without asking IT? All of this is possible with the Actian platform. 

Data scientists, analysts, and business users at any skill level can run BI queries, create reports, and perform advanced analytics with our platform with little or no IT intervention. We ensure quality, trusted data for any type of analytics use case. In addition, low-code and no-code integration and transformational capabilities make the Actian Data Platform user friendly and applicable to more analysts and more use cases, including those involving generative AI.  

Our patented technology continuously keeps your datasets up to date without affecting downstream query performance. With its modern approach to connecting, managing, and analyzing data, the Actian platform can save you time and money. You can be confident that data meets your needs to gain deep and rich insights that truly drive business results at scale.  

Experience Our Modern Data Platform for Yourself 

Our Actian platform offers the advantages your business needs—ease of use, high performance, scalability, cost effectiveness, and integrated data. We’ve listened to feedback to deliver a more user-friendly experience with more capabilities, such as an easy-to-understand dashboard that shows you what’s happening with consumption, along with additional metering and monitoring capabilities.   

It’s important to note that we’ve undertaken a major upgrade to our platform. This is not simply a rebranding—it’s adding new features and capabilities to give you confidence in your data to grow your business. We’ve been planning this strategic launch for a long time, and I am extremely proud of being able to offer a modern data platform that meets the needs of data-driven businesses and puts in place the framework to bring additional products onto the platform over time.  

I’d like you to try the platform for yourself so you can experience its intuitive capabilities and ultra-fast performance. Try it free for 30 days. You can be up and running in just a few minutes. I think you’ll be impressed.   

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The post Introducing The Actian Data Platform: Redefining Speed and Price Performance appeared first on Actian.


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Author: Vamshi Ramarapu

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