Risky Business: How to Balance Innovation & Risk in Big Data
Big data is a game-changer for organizations that use it right. However, a dynamic tension always exists between rapid innovation using big data and the high level of production maturity required for an enterprise implementation. Is it possible to find the right mix?
We say yes. Nik Rouda, senior big data analyst for Enterprise Strategy Group, reveals insights from his research and best practices for success. Join Nik and Zaloni’s Vice President of Product, Scott Gidley, for a discussion on how to find that balance between the lofty promises of big data and the mundane necessities of building a data lake environment that delivers business value.
Topics covered include:
- Big data business priorities and real-life use cases
- The range of people and organizations involved in big data projects
- A look at the time-to-business value that most organizations experience
- An overview of the qualities and capabilities desired in data lakes
- A typical data lake adoption lifecycle
- Zaloni’s Data lake 360 solution as a holistic approach to building and leveraging a big data lake
About the speaker:
ESG Senior Analyst Nik Rouda covers big data, analytics, business intelligence, databases, and data management. With 20 years of experience in IT around the world, he understands the challenges of both vendors and buyers, and how to find the true value of innovative technologies. Using the knowledge of strategic leadership that he gathered previously helping to accelerate growth for fast-paced startups and Fortune 100 enterprises, Nik’s goal is to strengthen messaging, embolden market strategy, and ultimately, maximize his client’s gain.
RecordedAug 25 201650 mins
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A majority of the data collected by organizations today is wasted. Whether through poor analytics, lack of resources, or just having too damn much of it. So how can organizations turn this around and actually start utilizing their data for powerful results?
By leveraging an X-360 initiative, companies are able to take their customer, product, patient, or other data and provide a 360-degree view using a governed and actionable data lake. By breaking down the silos associated with traditional data located in disjointed systems and databases, companies are finding new ways to improve loyalty programs, product development, marketing campaigns, and even find a new source of revenue from their data.
Join Jatin Hansoty, Director of Solutions Architecture at Zaloni, as he dives into real-world use cases from several of the world’s top companies. Learn from their architecture and the results they achieved.
Topics covered include:
- Best practices
- Common pitfalls to avoid
- Real-world use cases
- Future-proof architecture
Ryan Peterson, Global Technology Segment Lead at AWS & Scott Gidley, Vice President of Product at Zaloni
Today's enterprises need a faster way to get to business insights. That means broader access to high-value analytics data to support a wide array of use cases. Moving data repositories to the cloud is a natural step. Companies need to create a modern, scalable infrastructure for that data. At the same time, controls must be in place to safeguard data privacy and comply with regulatory requirements.
In this webinar, Zaloni will share its experience and best practices for creating flexible, responsive, and cost-effective data lakes for advanced analytics that leverage Amazon Web Services (AWS). Zaloni’s reference solution architecture for a data lake on AWS is governed, scalable, and incorporates the self-service Zaloni Data Platform (ZDP).
Join our webinar to learn how to:
- Create a flexible and responsive data platform at minimal operational cost.
- Use a self-service data catalog to identify enterprise-wide actionable insights.
- Empower your users to immediately discover and provision the data they need.
Achieving actionable insights from data is the goal of any organization. To help in this regard, data catalogs are being deployed to build an inventory of data assets that provides both business and IT users a way to discover, organize and describe enterprise data assets. This is a good first step that helps all types of users easily find relevant data to extract insights from.
Increasingly, end users want to take the next step in provisioning or procuring this data into a sandbox or analytics environment for further use. Attend this session to see how organizations are looking to build actionable data catalogs via a data marketplace, that allow self-service access to data without sacrificing data governance and security policies.
Learn how to provide governed access and visibility to the data lake while still staying on track and within budget. Join Scott Gidley, Zaloni’s Vice President of Product, as he discusses:
- Architecting your data lake to support next-gen data catalogs
- Rightsizing governance for self-service data
- Where a data catalog falls short and how to address
- Success use cases
As more organizations migrate to the cloud to take advantage of the cost efficiency, resiliency, scalability and flexibility that comes along with it; they’re finding the number of data processing options are staggering. Should they choose Spark over Presto? How about Redshift Spectrum over Athena?
Each have their own unique capabilities and might not be suitable for every scenario. Choosing the correct one can have a direct impact on an organization's bottom line.
Join Raj Rana, a Senior Solution Architect at Zaloni, as he discusses what it takes to successfully deploy the optimal AWS processing frameworks for a variety of situations.
Topics covered include:
- Current offerings in AWS
- Pricing models of each service
- What fits where? - considerations when choosing a processing framework
Data storage, data compute. Data ingestion. Metadata management. Governance. Visibility. Privacy. Transparency. These are just a few of the considerations you must plan for when modernizing your data platform with a data lake. It can be overwhelming, especially if you try to stitch specialized point products together yourself. Data lake implementations can get out of scope and out of control quickly.
Why pull your hair out trying to do it yourself? An actionable data lake is within reach. Join us as Nikhil Goel, Zaloni’s Lead Architect in Product Management, discusses the benefits that a turnkey data lake solution can provide as your data grows to meet your organization. Some of the topics covered will be:
• Storage and compute layers for cloud and on-premises
• Managed ingestion
• Zone-based data architecture
• Self-service access to the data catalog
• Customer success stories
Rajesh Nadipalli, Director of Product Support and Professional Services
Building a data lake is easy. Architecting a successful data lake that is flexible enough to accept multiple data sources, volumes, and types all while being able to scale with your business is harder.
Do it wrong and you've created a data swamp. Do it right and you turn data into the most valuable asset in your business.
Join us and learn from Rajesh Nadipalli, Zaloni’s Director of Product Support and Professional Services, how to:
- Set your data lake up for success with the right architecture
- Build guard rails to ensure the accuracy of data in your lake with proper data governance
- Provide visibility into your lake with a robust data catalog (or tie in with your favorite BI tools)
The introduction of the European Union’s (EU) General Data Protection Regulation (GDPR) mandates a paradigm change in the way organizations use personal data.
Elastic Stack is a suite of products which can help with GDPR compliance visibility. X-Pack access control for securing data access, Elasticsearch for indexing data for searches, X-Pack monitoring & alerting for data access events and REST APIs to manage the end to end privacy process.
Join this session with Sabyasachi Gupta, Lead Software Architect at Zaloni, to learn more about:
• GDPR primer - what is it and data in scope
• Different stages of handling GDPR personal data:
◦ Enforce privacy process
• How Elastic Stack realizes handling the stages of GDPR personal data
The modern, data-rich enterprise demands access to data at a pace that has outclassed traditional data management platforms. Whether they are utilizing a cloud, hybrid, or on-prem solution, these organizations require capabilities that are vendor-neutral and often implemented with microservices to ensure an agile environment at scale.
In this webinar, Scott Gidley, Zaloni’s Vice President of Product, will showcase the latest version of the Zaloni Data Platform. This version provides exciting new features to address the growing demands of data-driven companies, including:
- Managing hybrid and multi-cloud environments
- Managing your data with zones
- Cloud-native support
- Ingestion wizard
- Platform global search
- Persona-driven homepage
“Data is the new oil.” Just as we have to drill to get oil, we also need to mine data to get information out of it. Google, Facebook, Netflix and other titans of the digital era use data to build great products that touch every part of human life.
Regardless of scale, building a managed data lake on AWS requires a robust and scalable technical architecture. They often use microservices during the build process. A microservice architecture is centered around building a suite of small services focused on business capabilities and are independently deployable. It uses lightweight protocols and run on its own processes, which makes a microservice architecture ideal for building decoupled, agile, and automatable data lake applications on AWS.
Join this session with Sabyasachi Gupta, Software Architect at Zaloni, to learn more about:
- The what and why of a microservices architecture
- The different layers of a data lake stack
- Why is metadata important and how to capture it in AWS
- The relationship between Serverless and Microservices and available options on AWS
- How to build a data lake using microservice architecture on AWS
The three V’s of big data (velocity, volume, variety) continue to grow. There are more data types than ever, arriving faster, in sizes that traditional storage can barely keep up with. This is where transitioning to the cloud makes sense.
With its on-demand processing, storage scalability, and potential financial savings, the cloud is now a data-oriented organization’s dream. But what model is right for you? What challenges should you look out for? How do you migrate effectively?
Join Zaloni’s Director of Professional Services and Support, Raj Nadipalli, as he answers these questions - diving into cloud-based data lake use cases, a cloud-based data lake architecture, and more.
Topics covered include:
- Benefits of a cloud-based data lake (including hybrid and multi-cloud)
- Concerns with moving your data lake to the cloud
- Why metadata matters
- Cloud use cases
- A reference architecture
All roads lead to cloud: (almost) everyone knows that now. The benefits so outweigh the risks, that even the stodgiest enterprise architects now see the handwriting on the ceiling. While the rules are much different from the days of on-prem software, the reality is that smart cloud architects know their knowledge bar just went higher. How can you stay prepared? Check out this episode of Inside Analysis to hear host Eric Kavanagh interview several experts, including Parth Patel from Zaloni.
As new data sources continue to emerge, companies need to create “golden” or master records to achieve a single version of truth, as well as enriched views of customer or product data for applications such as intelligent pricing, personalized marketing, smart alerts, customized recommendations, and more.
By leveraging machine learning techniques in the data lake, you can integrate data silos and master your data for a fraction of the cost of a traditional master data management solution. Zaloni’s Data Master Extension uses a Spark-based machine learning engine to provide a unique solution for Customer or Product 360° initiatives at the scale of big data.
In this webinar, Scott Gidley, Zaloni’s Vice President of Product, will lead the discussion around:
- Using a machine learning approach for matching and linking records
- Implementing master data management natively in the data lake
- A practical example of master data in the data lake
Raj Nadipalli, Director of Product Support and Professional Services at Zaloni
As more and more organizations delve into the world of big data, they’re noticing that it’s not wise to dump data into a data lake without proper guardrails in place. Instead, companies need to architect and build their data lake with scalability, flexibility and governance in mind.
Based on hundreds of data lake implementations, Zaloni has built a reference architecture that has proven to be scalable and future-proof. This architecture is based on a zone approach through which data can live and travel throughout its lifecycle. This zone-based approach can greatly facilitate data governance and management, particularly if a data lake management platform, such as the Zaloni Data Platform, is in place.
How should these zones be defined within a data lake environment? What should happen to data within each of these zones? In this webinar, Raj Nadipalli, Director of Product Support and Professional Services at Zaloni, will answer these questions and address how to architect a data lake that is future-proof in the ever-changing big data ecosystem.
Matt Aslett, Research Director of Data Platforms & Analytics at 451 Research, and Kelly Schupp, VP of Marketing at Zaloni
Today, big data is enabling the advanced analytics that companies have dreamed of for driving their business. And as forward-thinking companies take advantage of big data and advanced analytics to drive digital transformation initiatives, it is forcing the laggards to realize that they will have to do the same if they want to survive.
The generally accepted architectural model for harnessing big data is a data lake. But data lakes, if leveraged simply as cheap storage within which to dump data, will inevitably disappoint. As the saying goes, garbage in, garbage out. Data lakes present unique challenges that must be dealt with if that big data set is going to be turned into actionable information.
So what does it take to succeed with a data lake? Why do some organizations get real value out of big data, while others struggle?
In this webinar, Matt Aslett, Research Director of Data Platform and Analytics at 451 Research and Kelly Schupp, VP of Data-driven Marketing at Zaloni, will discuss ideal data lake use cases such as Customer 360 and IoT. They will also discuss Zaloni’s data lake maturity model with which the data-eager company can chart its ideal course and roadmap.
Ben Sharma, CEO at Zaloni; Carlos Matos, CTO Big Data at AIG
Today's enterprises need broader access to data for a wider array of use cases to derive more value from data and get to business insights faster. However, it is critical that companies also ensure the proper controls are in place to safeguard data privacy and comply with regulatory requirements.
What does this look like? What are best practices to create a modern, scalable data infrastructure that can support this business challenge?
Zaloni partnered with industry-leading insurance company AIG to implement a data lake to tackle this very problem successfully. During this webcast, AIG's VP of Global Data Platforms, Carlos Matos, and Zaloni CEO, Ben Sharma will share insights from their real-world experience and discuss:
- Best practices for architecture, technology, data management and governance to enable centralized data services
- How to address lineage, data quality and privacy and security, and data lifecycle management
- Strategies for developing an enterprise-wide data lake service for advanced analytics that can bridge the gaps between different lines of business, financial systems and drive shared data insights across the organization
GDPR is quickly becoming a global data privacy crisis. With the May 2018 deadline looming, businesses in every industry are taking a fresh look at governing personal information. They’re finding out what’s needed to ensure compliance - and it’s not going to be easy.
Big data thought leader, Ben Sharma, has years of experience in data management and governance. He will discuss the impact GDPR has on big data management and explain how data lakes can set you up for success, both for GDPR compliance and future governance endeavors. This webinar will discuss specific technical solutions. If you are concerned about your GDPR compliance initiative, or just interested in verifying your current path, then this is a must-attend webinar.
- Data lineage
- Masking of PII
- Leveraging custom metadata
- Data lifecycle management
- Building a next-generation data architecture for compliance
- Your GDPR preparation checklist
In preparation for this deep dive into GDPR, we suggest you view our previous webinar on the basics of GDPR.
You know GDPR is coming. And with it are substantial penalties for noncompliance. What do you need to do to ensure that you are ready?
The General Data Protection Regulation (GDPR) is a European Union regulation set to go into effect May 25, 2018. This regulation requires that you strengthen data protection and management technologies and practices if you do business in the EU, have employees or customers that are EU citizens, or otherwise store or access data about European Union citizens. Among other things, GDPR addresses how personal data can be exported, the right for a citizen to control and delete their own personal data, data protection requirements and how data breaches are to be treated and a variety of other data and process-related rules and standards.
In this webinar, Kelly Schupp, Vice President of Marketing at Zaloni, will discuss where GDPR sits in the world of big data, overall data lake strategies that help with compliance, and how metadata management is key to that strategy.
- Metadata management
- GDPR compliance and best practices
- GDPR technologies
- Data lake governance
Scott Gidley, Vice President of Product Development at Zaloni
Today’s companies need actionable insights that are immediate. It is no longer feasible to wait weeks, even months, on IT to prepare business-critical data. Data lakes done right can enable you to view your entire data catalog at a moment’s notice and apply self-service transformations to that data. These interactions are key to providing a quick, clear understanding of business needs. But enterprises have a legitimate concern regarding data lake governance issues such as data privacy, data quality, security, and lineage. How do you marry both - how do you provide governed self-service to data in the data lake?
In this presentation, Scott Gidley, Vice President of Product Development at Zaloni, will highlight the benefits of governed self-service data and will provide a brief demo of Zaloni’s Self-service Data Platform.
- Metadata management, the foundation for governed self service in the data lake
- Data catalogs
- Self-service data preparation
- Self-service ingestion
- Bringing it all together with Zaloni’s Self-service Data Platform
Dirk Jungnickel, Senior Vice President of Business Analytics at du
Telco operators have worked with big data even before it had a name. By making data work for them, they have improved quality of service and customer satisfaction and have been some of the first companies to truly monetize their data.
Leveraging massive amounts of data has been a technical and architectural challenge. Most telco operators have adopted data lakes as cost-effective, highly scalable architectures for collecting and processing massive volumes of data and data types. Emirates Integrated Telecommunications Company (du), one of the UAE’s largest telecommunications companies, is addressing this issue with a game-changing modern data lake architecture.
Dirk Jungnickel explains how Dubai-based telco leader du leverages big data to create smart cities and enable location-based data monetization, covering business objectives and outcomes and addressing technical and analytical challenges.
Platform requirements for the IoT
Performing root cause analysis
The impact of data volume on pattern recognition
Zaloni simplifies data management for transformative business insights. We work with pioneering enterprises to modernize their data architecture and operationalize their data lakes to incorporate data into everyday business practices. The Zaloni Data Platform (ZDP) provides total control throughout the data pipeline from ingestion to analytics, with comprehensive data management, governance and self-service data preparation capabilities for IT and business users. A leader in big data for more than a decade, Zaloni’s expertise is deep, spans multiple industries, and has proven invaluable to customers at many of the world’s top companies. We are proud to be recognized by CRN’s 2018 Big Data 100 list, Forbes top 20 big data companies to work for, and Red Herring’s Top 100 North America Award.