Tendü Yogurtçu, PhD

I sat down for a captivating conversation with Ravit Jain on #TheRavitShow. We talked about the importance of trusted data for AI success, the challenges and implications of neglecting data quality, and AI predictions for 2024.

In 2024, I expect organisations to continue implementing #AI to increase efficiency in both the back and front office, while exploring how generative AI can create new capabilities, products, and services. In the process, businesses will increasingly realise that #data is central to their AI success.
We, at Precisely, predict a future where accurate, consistent, and contextual data drives AI success.

Financial services has been using traditional AI techniques for many decades. Like many industries, we can expect financial technology to expand the use of AI and #GenAI in 2024. In addition to common use cases for fraud detection, anti-money laundering, mitigating risk, and identifying trends and forecasting, we are likely to see increased adoption of natural language interfaces and more automation with market research, customer service and back-end compliance work. These use cases will drive… Mehr zeigen

Financial services has been using traditional AI techniques for many decades. Like many industries, we can expect financial technology to expand the use of AI and #GenAI in 2024. In addition to common use cases for fraud detection, anti-money laundering, mitigating risk, and identifying trends and forecasting, we are likely to see increased adoption of natural language interfaces and more automation with market research, customer service and back-end compliance work. These use cases will drive focus on data, governance, and cybersecurity. Weniger anzeigen

Whether through the recent United Nations Framework Convention on Climate Change (COP27) or protest initiatives such as Just Stop Oil, conversation around organizations’ environmental, social and governance (ESG) efforts is hot. There are no two ways about it, insurers have to be at the forefront of this conversation.

In 2022, our world will not only become increasingly data-driven, it will also become fueled by better, smarter, and contextualized data. As data ecosystems grow and are bolstered by the insights derived from enhanced AI/ML capabili­ties, we’ll see the businesses that are invest­ing in these technologies making more informed decisions and surpassing their competitors at an exponential rate.

An interview about career development, turning challenges into opportunities, and tips for early-in-career people.

Data Predictions For 2022

Before AI/ML can contribute to enterprise-level transformation, organizations must first address the problems with the integrity of the data that is driving AI/ML outcomes. The truth is, companies need trusted data, not just big data. That’s why any discussion about AI/ML is also a discussion about data integrity.

As we continue to struggle with the Delta variant of COVID-19, women are questioning what else we can and should be doing. Tendu Yogurtcu has spent much of career dealing with issues facing women in technology but even as she oversees technology at Precisely, a global leader in data integrity, she wonders what else she should be doing for women.

Digital transformation has been a consistent drumbeat in the industry for the past few years and is a core piece of many enterprises’ business strategies. Successful digital transformation is the primary differentiator in today’s business landscape, and yet many organizations are struggling with the digitization. The companies with a data strategy — making data and analytics the center of their business strategy and relying on data to make better decisions and drive better insights — are the… Mehr zeigen

Digital transformation has been a consistent drumbeat in the industry for the past few years and is a core piece of many enterprises’ business strategies. Successful digital transformation is the primary differentiator in today’s business landscape, and yet many organizations are struggling with the digitization. The companies with a data strategy — making data and analytics the center of their business strategy and relying on data to make better decisions and drive better insights — are the ones succeeding with their digital transformation. Weniger anzeigen

We’re all aware that women are underrepresented in the field. But what’s even more troubling is the leadership gap: Recent Gartner research revealed that only 22% of IT leaders are women.
I’m part of that 22%. As a CTO, I’m also a member of an even smaller group of female C-suite tech executives (which another Gartner study found hovers around 13%). That’s not only unfortunate but also dangerous. Without women in senior roles, we have no hope of closing the tech gender gap -- not to mention,… Mehr zeigen

We’re all aware that women are underrepresented in the field. But what’s even more troubling is the leadership gap: Recent Gartner research revealed that only 22% of IT leaders are women.
I’m part of that 22%. As a CTO, I’m also a member of an even smaller group of female C-suite tech executives (which another Gartner study found hovers around 13%). That’s not only unfortunate but also dangerous. Without women in senior roles, we have no hope of closing the tech gender gap -- not to mention, we’re missing out on untold innovative thinkers and ideas.
So, how do we work toward closing this gap? Weniger anzeigen

An @EarlyAdopterEAR Podcast on blockchain, the importance of the Hyperledger project, along with other key trends in BI & analytics.

Cloud computing has evolved to the point where most enterprises have, to one degree or another, deployed cloud workloads. Our 2018 Cloud Survey found 70 percent of over 900 IT professionals use cloud services. But as enterprises see the benefits – namely business continuity, IT efficiency, elasticity and the pay-as-you-go billing model – business challenges remain. This article discusses strategies for a successful cloud adoption.

Inside Analysis President, Eric Kavanagh, interviews Tendu Yogurtcu of Syncsort about the state of today’s enterprise and how Syncsort provides specialized solutions to …

Sharing thoughts on why strong Data Quality is the key to success with Machine Learning, artificial intelligence and blockchain.

Sharing insights on the top tech trends for 2019, why Data Governance is key & best practices for Blockchain, Machine Learning and more.

How Syncsort Uses Conway's Law To Accelerate And Control Product Evolution by Dan Woods - Interview with Dr. Tendu Yogurtcu

Discussing Mega Trends driven by Advanced Business and Operational Analytics: Cloud, Streaming, Data Science and Data Governance.

Executive round table on big data adoption in FinServ and Insurance - hosted by Tendu Yogurtcu and Amr Awadallah, CTO of Cloudera.

Discussing the importance of data quality, data governance in the data lake.

If your business has legacy data on legacy systems, you’re likely struggling to fully and truly integrate that data into your broader analytic/BI deliverables.
That’s a big problem—even if you’re not directly responsible for legacy systems—because siloed data inevitably compromises all your analytics and BI efforts. It can also compromise data governance and security. So how can you leverage legacy data in ways that are sufficiently easy, agile, reliable and performant?

How companies are using data is changing, marking the advancement of tools and the investment from executive leadership of forecasting more parts of the business. To touch on the changing Big Data market, this article discusses five major trends.

By understanding some of the biggest Big Data obstacles, companies can prepare ways to avoid them.

Progressive's journey to modern #data architecture #bigdata #DWS17

Executive panel highlighting challenges and opportunities for women in technology.

Panell on #bigdata, challenges & opportunities for the businesses #dataintegration #dataquality

Artificial Intelligence in financial services is not a new idea – and depending on your definition of machine learning, one can argue that AI has been part of the industry for decades now. As AI begins to converge with Big Data, the financial services industry is being radically transformed through advanced analytics in ways that promise smarter solutions across the board.

The concept of a data lake is now commonplace, as businesses realise the value of having a single repository to house all enterprise data in its original, unaltered format. While this is a vital first step in mastering a single view of all data assets, left unchecked, it can turn into a data swamp.

Syncsort and Hortonworks joint solution offering for Enterprise Data Warehouse (EDW) optimization empowers our customers to transform scarcity of trust, value, insights, and skills into abundance in order to become a data centric organization.

Data integration, discovery and integrity - discussing latest state of the data integration market and how organizations can prevent data lakes turning into data swamps.

To truly “master” all of a company’s data in an environment where they can react quickly to business needs, companies must first liberate all enterprise data, especially hard-to-access data from legacy platforms like the mainframe which houses the most critical data assets such as customer data. Organizations must then integrate these core data assets with the emerging new data sets from the Internet of Things (IoT) and cloud.

"Mostly companies are missing out on revenue since the value of IoT data largely depends on creative use of this data and effective insight when assessing IoT revenue opportunities. There are many ways that businesses can better leverage IoT data for revenue opportunities. Here are six tips for making the most of it."

Hadoop Summit San Jose, CA – theCUBE: Update on Partnership with Hortonworks, Syncsort’s competitive differentiation in the Hadoop Data Integration space and why Hortonworks chose DMX-h as their ETL of choice, June 2016

Hadoop Summit San Jose, CA – Technical Track Presentation by Tendu Yogurtcu & Scott Gnau, Hortonworks CTO: Use Cases from Batch to Streaming, MapReduce to Spark, Mainframe to Cloud, Todays ETL Does it All

Interview - The Voices and View from FemTech Leaders
On leadership, importance of mentorship and having a female role model...

This week, Hortonworks announced an exciting expansion of our long-standing partnership. Hortonworks will now resell Syncsort’s leading Hadoop data integration software, DMX-h for onboarding ETL processing in Hadoop. DMX-h will enable our joint customers to easily access and collect data from a diverse set of enterprise data sources, including RDBMSs, mainframe and emerging streaming data sources, bringing all of the data to the Hortonworks Data Platform (HDP™) for bigger insights and to drive… Mehr zeigen

This week, Hortonworks announced an exciting expansion of our long-standing partnership. Hortonworks will now resell Syncsort’s leading Hadoop data integration software, DMX-h for onboarding ETL processing in Hadoop. DMX-h will enable our joint customers to easily access and collect data from a diverse set of enterprise data sources, including RDBMSs, mainframe and emerging streaming data sources, bringing all of the data to the Hortonworks Data Platform (HDP™) for bigger insights and to drive business agility. Weniger anzeigen

At a macro level, organizations have never had more tools available to integrate their enterprise data for meaningful insights, especially with powerful compute frameworks like Hadoop and Spark. However, accessing, integrating and managing data from all enterprise sources – legacy and new – still proves to be a challenge.This article discusses how to prioritize initiatives in order to maximize ROI.

BigData SV San Jose, CA – theCUBE: Interview with George Gilbert and John Furrier on Next Gen Data Warehouse, Batch and Real-Time Use Cases

Spark Summit East 2016, NY - theCUBE – Interview with Dave Vellante and George Gilbert on Convergence of Batch and Operational Analytics, Real-Time Analytics

Keeping track of data, data security, data access, and regulatory compliance are more critical and more challenging than ever before. Data governance in Hadoop — including auditing, lineage, and metadata management — requires a scalable approach that is easy to interoperate across multiple platforms.

BigData NYC 2015 – theCUBE: Interview with Dave Vellante and George Gilbert on Big Data Trends

Vision Blog - Cloudera
Innovations to enhance Apache Spark’s value proposition and Syncsort's Hadoop products that are part of Cloudera’s Accelerator Program for Spark

Big data has been a reality for a few years now and has been part of the planning process for 2015 budgets for many enterprises. This article discussed what enterprises expect to achieve from their efforts with big data in the next year or so.

BigDataSV 2015 – theCUBE: Interview with Jeff Kelly and John Furrier on Hadoop Adoption, February 2015

This blog expands on Syncsort’s integration with Apache Ambari, being the first data integration solution to use Ambari Stacks, creating a unified user experience for deployment, management and monitoring across Hadoop clusters.

This article discusses why there are so few women pursuing technology oriented careers and how do we remedy this problem.

As Hadoop takes its place as a data processing platform, one of the major challenges is data ingestion. The enterprise applications require integrating data from many sources, where these sources often originate from multiple platforms.This blog discusses how Syncsort's solutions help with these challenges and provides details on Syncsort's submission (SQOOP-1272) to extend Apache Sqoop for transferring data from Mainframe to Hadoop,

Tools for offloading expensive workloads from traditional data warehouse to Hadoop; and prepare data for analytics and SQL over Hadoop.

Challenges in Big Data adoption and opportunities for start-ups to offer solutions optimized for the business user.

Challenges and opportunities in Big Data adoption

Tech hiring trends vary year by year. The top IT hiring trends for 2014 include the driving need for IT security, the boom of big data, and more people embracing the cloud.
TechRepublic talked to several IT executives and tech recruiters in a roundtable to find out what they predict in tech hiring this year.

Perspectives on Hadoop 2, having a technical ‘whole’ product and crossing the chasm.

A recap of Hadoop Summit. YARN was definitely the largest topic of discussion, but there were also a number of discussions around performance, file formats, security, and more.

This blog shares results of Hadoop Terasort benchmark with Syncsort’s Hadoop product, DMX-h.

The Apache Hadoop 2.0.3 includes a new feature -- pluggable map and reduce-side sort implementations. In some cases, a full-sort of data isn't required on the reduce side -- e.g. a hash-based grouping could be enough. This blog post details use-cases enabled by the new pluggable sort feature.

Enterprise data warehouse optimization, how to get legacy data into data lake, data governance.