“Analytics help organizations harness big data and use it to identify new opportunities. And the starting point for effective analytics is applying new techniques to discover, prepare and govern data,” said Tapan Patel, Senior Marketing Manager for AI and Analytics at SAS. “New SAS Viya data management offerings allow businesses to catalog assets across the cloud and on-premises and prepare data without hassle. These are fundamental elements of a successful analytic journey.”

Most analytics professionals spend too much time on data preparation rather than building models and delivering analytic insights for their organizations. Whether data is simple or complex, organizations need innovative solutions that cut through the chaos, provide flexibility and efficiently transform data to create better analytical assets. Today, SAS is announcing two such innovative solutions.

SAS Studio Analyst
As analytics and AI become more embedded in day-to-day operations, organizations need data in the right place, in the right condition and at the right time.

Now available in SAS Viya, SAS Studio Analyst empowers data scientists and data analysts with a self-service environment to expedite delivery of trusted data for analytics. SAS Studio Analyst allows users to visually represent, prebuilt or custom, data quality and data preparation steps as part of the flow, which can be easily reused and managed. This helps to jump-start analytics initiatives and efficiently orchestrate data needed for it.

SAS Information Governance
In a world with endless data sources, many organizations struggle to grasp all data that is available, identify the contents of a data set, and evaluate data for analytics fitness. And as the amount of data increases from more and more sources, these issues are compounded, affecting the value of analytical outputs.

SAS Information Governance, also now available in SAS Viya, provides an intuitive data catalog and metadata search facility for analyst, business and IT users to ingest, discover and manage data resources, while simultaneously governing and protecting data. With the solution, data professionals can spend less time searching and organizing data, and more time on actual analysis.

Better data management and governance improves people’s health
Riverside County in Southern California relies on data integration and analytics from SAS to improve the health and well-being of more than 2.5 million residents. The county faced the challenge of pulling together innumerable amounts of data from multiple sources. The goal is to better serve the needs of its diverse and large population through the county’s health system, which includes a large medical center, an inpatient psychiatric facility and several health care clinics.

To ensure the most vulnerable populations receive coordinated medical, behavioral health and socioeconomic services, Riverside County worked with SAS to design a solution that combines data preparation, advanced analytics and data visualization capabilities. The solution, powered by SAS Viya, enables the county to integrate health and non-health data from its public hospital, county jail, and behavioral health, social services and homelessness systems.

By connecting these databases, Riverside County can now see how individuals interact with different services across its health system and map care pathways to health outcomes. This is enhanced by entity resolution, a feature of the technology that enables the county to identify unique entities, even if a person’s name, address or other personal identifiers don’t match up across different databases.

“Before SAS, we had a massive data integration problem,” said Judi Nightingale, Director of Population Health at Riverside County. “If we can get an integrated look at every client and reduce our siloed efforts, we can get everyone in the county to their health and wellness goals more quickly.”

Read the full story of how Riverside County tapped SAS Viya to improve the health and well-being of vulnerable Californians at sas.com/en_us/customers/riverside-county.html.

The latest release of SAS Viya includes the new data management offerings – SAS Studio Analyst and SAS Information Governance – and is designed to be delivered and updated continuously. The cloud-native software enables customers to efficiently democratize analytics throughout their organizations, while seamlessly managing analytic workloads and embedding analytics into variety of operational applications for making confident decisions.

Image Licensed by: Pixabay.com

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MySQL is recognized as the most popular database on the planet¹ and is used by the world’s largest social networks, ecommerce companies, and banks, as well as the most innovative manufacturers and high-tech companies. While MySQL databases are commonly used for OLTP, most enterprises that run MySQL databases also need to run analytics on data stored in MySQL databases. Until today, organizations had to extract, transform, and load (ETL) their data into a separate analytics database – a costly and complex process that reduces performance, security, and data quality, delaying the deployment of new applications.

The Oracle MySQL Database Service with the MySQL Analytics Engine provides a fully managed scale-out service for analytics and OLTP and is the only service that enables customers to run OLTP and OLAP workloads directly from their MySQL database. When users spin up the service, data from the MySQL database is populated in the memory of the analytics engine, eliminating the need to ETL data to specialized databases. The service works seamlessly with any MySQL-compatible tools and applications and will automatically route queries to the MySQL Analytics Engine, dramatically improving performance. Any changes to the MySQL database are automatically populated into the analytics engine in real-time. This simplifies application development, saves time, enables real-time queries, decreases costs, and improves security. The new service is available across all Oracle Cloud commercial regions and will be available in Oracle Dedicated Region Cloud@Customer.

“MySQL is the most popular database among developers and is widely used by companies across industries. But, until today, MySQL users have been forced to move their data into separate incompatible data warehouses for analytics leading to higher costs and delayed answers,” said Edward Screven, chief corporate architect, Oracle. “With the MySQL engineering team’s latest innovations, Oracle is the only provider that offers developers and database administrators a single, unified platform that can easily run high performance real-time analytics against their MySQL database without requiring any change to their MySQL applications – making Oracle Cloud Infrastructure the best place to run MySQL applications.”

The MySQL Database Service is a fully managed database cloud service that enables customers to provision MySQL databases in minutes and focus on development, without having to worry about time-consuming database administration tasks such as scaling, backup, OS patching, and server maintenance. The MySQL Database Service is the only public cloud service built on MySQL Enterprise Edition to help ensure the highest reliability and security. The new service is completely compatible with on-premises MySQL, making it easy for customers to move existing MySQL applications and workloads to Oracle Cloud. As a result, developers always have access to the latest MySQL features, and can leverage native services in OCI using technologies such as Kubernetes and Docker.

The MySQL Analytics Engine is architected for massive scale and performance, accelerating MySQL performance by 400 times for analytic queries. The analytics engine offers in-memory hybrid columnar processing, massive inter- and intra-node parallelism optimized for Oracle Cloud Infrastructure, and distributed query processing algorithms while relieving DBAs of time-consuming ETL tasks.

“I had never considered MySQL for data warehousing – until now. The Oracle MySQL Database Service with its integrated Analytics Engine can now be used for both transaction processing and analytics,” said Richard Winter, CEO of WinterCorp. “With its in-memory parallel architecture, the MySQL Database Service will now process queries much faster, enabling a new generation of open source, analytic database applications.”

Simplicity, Performance, and Cost Savings Separate Oracle MySQL Database Service from the Pack 

“At Siemens Healthineers we use several MySQL databases. During our tests of the new MySQL Database Service Analytics Engine we discovered astonishing performance improvements, reducing query times from hours to literally seconds in cases of non-index based queries,” said Dr. Jens Uecker, senior key expert, Siemens Healthineers. “This enables us to expand service to new levels and opens the door to many more analytics-based capabilities, all while maintaining a single, seamless database platform.”

“The MySQL Database Service Analytics Engine surprised us by improving query performance significantly without modifying any queries or using any ETL tools,” said Yoshihiko Goto, Service Front Team, Server Infrastructure Group, DMM.com LLC. “This fully managed analytics platform makes it possible for us to focus more on innovating e-commerce business services.”

Kenichi Sasaki, SRE team of Japan at Mercari, Inc. said, “The performance of the MySQL Database Service Analytics Engine is over 20 times faster than the analytics service of one of the largest cloud vendors, and accelerates our analytics workload by 45,000 times compared to MySQL on-premises.”

• OCI customers can now run sophisticated analytics directly against their operational MySQL databases, eliminating the need for complex and expensive data integration with a separate analytics database
• MySQL Analytics Engine is an in-memory analytics accelerator that automatically scales out to thousands of OCI cores and at least 2X faster and up to 66% less expensive than Amazon Redshift
• Unified operational and analytics MySQL service makes OCI the best place to build and run MySQL applications

Image licensed by Pixabay.com

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1. Reconfiguring the cloud for analytics
   “Originally the cloud was built for transactional systems. It wasn’t built for analytics. Analytics requires a lot more memory than a traditional application – and faster networks to get to data that is not in memory – in order to make analytics work in real time. Those are things cloud providers didn’t think about because initial applications in the cloud were transactional.”
        –  Tom Fisher, Senior Vice President of Business Development, SAS
2. Decision makers start to trust AI
   “The more visibility that decision makers have into AI results, the more confidence they have in the decisions that are being made by the models. Adding human oversight and explaining the models at each step in a decision process will start to bring acceptance to AI and automated decisioning.”  
        –  João Oliveira, Business Solutions Manager, SAS
3. Smart towns catch up to smart cities
   “As city dwellers flee the city, they expect the same levels of service in the country, including fast broadband, food delivery and digital interaction with government agencies and civic planners. Small towns are catching up with cities using analytics. Now that where you work no longer matters, smaller cities have an opportunity to attract and recruit people to relocate using analytics, driving population growth that was previously unattainable.”
        –  Shaun Barry, Senior Manager, Global Security Practice, SAS
4. The year of the vaccine
   “If 2020 was the year of COVID, 2021 will be the year of the vaccine. Which vaccine will be approved first? Which will get distributed around the globe? Will we rely on multiple vaccines to improve distribution and effectiveness? Analytics will not only play a role in approvals for the vaccine development process but will also be important for planning rollout and tracking distribution, side effects and effectiveness.”
        –  Greg Horne, Global Principal for Health Care, SAS
5. Consumers gain more control with remote everything
   “Consumers are in control when it comes to retail digitization, banking digitization, health care digitization – and more. Work, school, lectures, concerts, book readings, religious services, fitness workouts: If it can go remote, it is going remote. As consumers do more online, businesses are expected to keep up. That means improved digital technologies, more efficient supply chains, online customer service and easy scheduling – all managed and optimized with analytics. The benefit to the business? If you can digitize quickly, you’ll have more data and a better view into who’s interested in your content, products and services.” 
        –  Klaus Kohlmayr, Chief Evangelist, IDeaS
6. Data natives enter the workforce
   “A generation raised on data – from eating and exercising to sleeping and productivity – is beginning to enter the workforce. Their innate abilities to track and understand data will improve the ways we work. They bring data literacy skill sets and a comfort level with data that will help make all aspects of organizations more analytical and more innovative with data.” 
        –  Lucy Kosturko, Manager for Social Innovation, SAS
7. Patient-first pharma saves more lives
   “The data-heavy drug development process continues to improve with advanced analytics – and all of the improvements benefit patients. Due to advancements in analytics, for example, clinical trials are able to bucket multiple drugs into one study instead of only studying one drug at a time. Targeted therapies based on your genetic profile are becoming easier to develop. And results from every phase of clinical trials are coming in faster and faster, giving patients a better opportunity to find the latest treatments that will work for them.” 
        –  Mark Lambrecht, Director of Global Health and Life Sciences, SAS
8. Old-school organizations have new opportunities to reinvent themselves with analytics
   “Data-driven government responses to COVID-19, for example, are changing perceptions of government responsiveness. And banks that implement automated decisions are surprising customers with new investment opportunities. Today, the industry that invented analytics is showing that it can apply analytics in new ways to help citizens.”
        –  Steve Bennett, Director of Public Sector and Financial Services, SAS

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Ash Ashutosh, Actifio CEO and Co-Founder, said, “We used to worry about the digital divide — those who have access to the internet and those who don’t. Today, it’s the data divide — the divide between organizations that know how to leverage and exploit their data and accelerate the business, and those that don’t. This year, that divide has had a major effect. Data is the new infrastructure, and more and more of our customers are on the right side of the digital divide.”

This is reinforced by IDC analyst Archana Venkatraman’s newly published guest blog, sponsored by Actifio and titled, “Innovate with Data in the Next Normal: Leveraging cloud data management platforms for data protection, availability, and re-use. With IDC estimating the amount of data created over the next three years to exceed the amount created over the last 30 years, “Maximizing the value of data is a foundational aspect of achieving a data-driven organization,” the analyst asserts. “Today, there is a laser-sharp focus on value and cost optimization. As a result, enterprises need to pivot from traditional backup environments that are seen as necessary, single-use, static business procedures to a new paradigm of backup as a dynamic data hub that can provide any data, any number of times, for any business purpose – DevOps, analytics, testing, simulation, machine learning, or app development.”

Ashutosh continued, “I think this is a phenomenal time for companies to absolutely go change, make this transformation about data acceleration, data leverage, data exploitation. And this idea of making data the new infrastructure, it’s finally come to fruition. Most of our customer base relies on Actifio for secure backup and then re-uses the backup data for things that accelerate the business, make the business move faster and more productively.”

“Backup cannot be an insurance or a destination,” Ashutosh said. “It has to be something that you can use as an asset. For us, being the world’s fastest backup and most scalable DR solution is a starting point. It really pays off when customers can use that to develop applications 8-10 times faster, to run analytics 100 times faster. The more data you have, the more people who use the data you have, the better this return becomes.”

In her report, Venkatraman describes IT organizations’ urgency: “In conversations with IDC, IT teams insist that live data availability, data reuse, and data cost optimization are moving from nice-to-have to must-have capabilities for their businesses. But many businesses were caught by the pandemic with legacy data management architectures that were neither cloud connected or automated. These architectures hindered quick access to data, becoming bottlenecks that slowed business decisions. At some organizations, refreshing a large database environment could take as many as  three days. This needs to change.”

Actifio’s patented Virtual Data Pipeline (VDP) technology turns data silos into data pipelines, with automation from on-premises to any cloud for secure, instant access for business use.

Image licensed by Pixabay.com

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The “Scaling up AI across the life science value chain: Enhancing R&D, creating efficiencies and increasing impact” report summarizes key findings from that survey, and offers recommendations for how life sciences companies can gain immediate returns on investment and experience a competitive advantage over the longer term.

From R&D to manufacturing, supply chain to commercial functions, AI is beginning to have an impact on increasing efficiencies across the biopharma value chain, especially as a result of the COVID-19 pandemic. In addition, increased remote work environments helped life sciences leaders realize how effective digital solutions can be in helping their businesses run smoothly, transforming mindsets and enabling executives to lean into a future grounded in digitization, data and AI. While today AI is primarily applied to automate existing processes, additional potential lies in accelerating insights and discovery to expedite access to new therapies and products. AI’s potential stretches across the value chain from identifying and validating genetic targets for drug development, designing novel compounds, expediting drug development, making supply chains smarter and more responsive, to helping launch and market products. Life sciences companies that deploy AI strategically across the entire enterprise will likely be best positioned to maximize their AI investments and achieve a competitive edge.

“The life sciences industry has only begun to scratch the surface of AI’s potential but the good news is biopharma and life sciences leaders see the potential and are willing to make the investments necessary to realize what’s possible. They should be cautious, though, and carefully plan and strategize so those investments are used wisely and result in the desired outcomes. By spending time on a solid strategy, putting the building blocks in place for success and leveraging relationships with relevant partners, AI can help transform the life sciences industry as we know it and get the necessary products to market more quickly,” said Aditya Kudumala, principal, Deloitte Consulting LLP.

Investing in AI
Biopharma and medtech leaders surveyed agree that life sciences organizations are investing in AI, but “how” they’re investing varies widely. When asked about their company’s investments in AI projects and technologies in the past year:

• Forty-one percent invested $20-50 million; followed by 26% that invested $10-20 million; and 21% that invested more than $50 million in AI initiatives.
• More than half of survey respondents expect investments in AI will continue to increase throughout 2020 as AI moves from tactical improvements in efficiency to larger-scale, organization-wide projects.
• Forty-six percent of respondents said it takes longer than expected to receive payback from investments in AI initiatives.

Enhanced efficiency
When it comes to the top outcomes life sciences companies hope to achieve by using AI, three primary objectives emerged:

1. Enhance existing products (28%)
2. Create new products and services (27%)
3. Make processes more efficient (22%)

The top three outcomes where respondents said they’ve seen the most success with AI include:

1. Making processes more efficient (43%)
2. Improving decision making (41%)
3. Enhancing existing products and enabling new business models (both 40%)

Understanding risks
As with any new technology, survey respondents pointed to multiple challenges associated with AI implementation, including poor-quality data, siloed data systems, integrating AI into legacy systems and risk management. The top challenges life sciences companies cited when implementing AI were:

• Identifying use cases with the greatest business value (30%)
• Integrating AI into the organization (28%)
• Data challenges (28%)
• Challenges implementing AI technologies (28%)

Moving AI forward 
In order to take AI to the next level, Deloitte recommends life sciences leaders consider the following three step process:

• First, company leaders should define their vision and strategy for how they want to take advantage of AI and what they seek to achieve from their investments in data, analytics and AI.
• To carry out that strategy, companies should then assemble the building blocks to help set themselves up towards success. The core building blocks Deloitte advises leaders to consider include: technology and data, technology architecture, ecosystems and alliances, talent and aligning on risk management.
• Third, leaders should evaluate ways to scale up internal investments or partnerships that can help their companies go from short-term to longer-term success in the market.

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