Welcome!

Related Topics: @BigDataExpo, @CloudExpo, @ThingsExpo

@BigDataExpo: Blog Feed Post

Data Unification at Scale | @CloudExpo #BigData #DataLake #AI #Analytics

This term Data Unification is new in the Big Data lexicon, pushed by varieties of companies

This term Data Unification is new in the Big Data lexicon, pushed by varieties of companies such as Talend, 1010Data, and TamR. Data unification deals with the domain known as ETL (Extraction, Transformation, Loading), initiated during the 1990s when Data Warehousing was gaining relevance. ETL refers to the process of extracting data from inside or outside sources (multiple applications typically developed and supported by different vendors or hosted on separate hardware), transform it to fit operational needs (based on business rules), and load it into end target databases, more specifically, an operational data store, data mart, or a data warehouse. These are read-only databases for analytics. Initially the analytics was mostly retroactive (e.g. how many shoppers between age 25-35 bought this item between May and July?). This was like driving a car looking at the rear-view mirror. Then forward-looking analysis (called data mining) started to appear. Now business also demands "predictive analytics" and "streaming analytics".

During my IBM and Oracle days, the ETL in the first phase was left for outside companies to address. This was unglamorous work and key vendors were not that interested to solve this. This gave rise to many new players such as Informatica, Datastage, Talend and it became quite a thriving business. We also see many open-source ETL companies.

The ETL methodology consisted of: constructing a global schema in advance, for each local data source write a program to understand the source and map to the global schema, then write a script to transform, clean (homonym and synonym issues) and dedup (get rid of duplicates) it. Programs were set up to build the ETL pipeline. This process has matured over 20 years and is used today for data unification problems. The term MDM (Master Data Management) points to a master representation of all enterprise objects, to which everybody agrees to confirm.

In the world of Big Data, this approach is very inadequate. Why?

  • Data unification at scale is a very big deal. The schema-first approach works fine with retail data (sales transactions, not many data sources,..), but gets extremely hard with sources that can be hundreds or even thousands. This gets worse when you want to unify public data from the web with enterprise data.
  • Human labor to map each source to a master schema gets to be costly and excessive. Here machine learning is required and domain experts should be asked to augment where needed.
  • Real-time data unification of streaming data and analysis can not be handled by these solutions.

Another solution called "data lake" where you store disparate data in their native format, seems to address the "ingest" problem only. It tries to change the order of ETL to ELT (first load then transform). However it does not address the scale issues. The new world needs bottoms-up data unification (schema-last) in real-time or near real-time.

The typical data unification cycle can go like this - start with a few sources, try enriching the data with say X, see if it works, if you fail then loop back and try again. Use enrichment to improve and do everything automatically using machine learning and statistics. But iterate furiously. Ask for help when needed from domain experts. Otherwise the current approach of ETL or ELT can get very expensive.

  • LikeData Unification at scale
  • Comment
  • ShareShare Data Unification at scale



Read the original blog entry...

More Stories By Jnan Dash

Jnan Dash is Senior Advisor at EZShield Inc., Advisor at ScaleDB and Board Member at Compassites Software Solutions. He has lived in Silicon Valley since 1979. Formerly he was the Chief Strategy Officer (Consulting) at Curl Inc., before which he spent ten years at Oracle Corporation and was the Group Vice President, Systems Architecture and Technology till 2002. He was responsible for setting Oracle's core database and application server product directions and interacted with customers worldwide in translating future needs to product plans. Before that he spent 16 years at IBM. He blogs at http://jnandash.ulitzer.com.

Latest Stories
WebRTC is great technology to build your own communication tools. It will be even more exciting experience it with advanced devices, such as a 360 Camera, 360 microphone, and a depth sensor camera. In his session at @ThingsExpo, Masashi Ganeko, a manager at INFOCOM Corporation, will introduce two experimental projects from his team and what they learned from them. "Shotoku Tamago" uses the robot audition software HARK to track speakers in 360 video of a remote party. "Virtual Teleport" uses a...
Any startup has to have a clear go –to-market strategy from the beginning. Similarly, any data science project has to have a go to production strategy from its first days, so it could go beyond proof-of-concept. Machine learning and artificial intelligence in production would result in hundreds of training pipelines and machine learning models that are continuously revised by teams of data scientists and seamlessly connected with web applications for tenants and users.
When shopping for a new data processing platform for IoT solutions, many development teams want to be able to test-drive options before making a choice. Yet when evaluating an IoT solution, it’s simply not feasible to do so at scale with physical devices. Building a sensor simulator is the next best choice; however, generating a realistic simulation at very high TPS with ease of configurability is a formidable challenge. When dealing with multiple application or transport protocols, you would be...
IT organizations are moving to the cloud in hopes to approve efficiency, increase agility and save money. Migrating workloads might seem like a simple task, but what many businesses don’t realize is that application migration criteria differs across organizations, making it difficult for architects to arrive at an accurate TCO number. In his session at 21st Cloud Expo, Joe Kinsella, CTO of CloudHealth Technologies, will offer a systematic approach to understanding the TCO of a cloud application...
"With Digital Experience Monitoring what used to be a simple visit to a web page has exploded into app on phones, data from social media feeds, competitive benchmarking - these are all components that are only available because of some type of digital asset," explained Leo Vasiliou, Director of Web Performance Engineering at Catchpoint Systems, in this SYS-CON.tv interview at DevOps Summit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
SYS-CON Events announced today that Secure Channels, a cybersecurity firm, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Secure Channels, Inc. offers several products and solutions to its many clients, helping them protect critical data from being compromised and access to computer networks from the unauthorized. The company develops comprehensive data encryption security strategie...
SYS-CON Events announced today that App2Cloud will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct. 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. App2Cloud is an online Platform, specializing in migrating legacy applications to any Cloud Providers (AWS, Azure, Google Cloud).
The goal of Continuous Testing is to shift testing left to find defects earlier and release software faster. This can be achieved by integrating a set of open source functional and performance testing tools in the early stages of your software delivery lifecycle. There is one process that binds all application delivery stages together into one well-orchestrated machine: Continuous Testing. Continuous Testing is the conveyer belt between the Software Factory and production stages. Artifacts are m...
WebRTC is the future of browser-to-browser communications, and continues to make inroads into the traditional, difficult, plug-in web communications world. The 6th WebRTC Summit continues our tradition of delivering the latest and greatest presentations within the world of WebRTC. Topics include voice calling, video chat, P2P file sharing, and use cases that have already leveraged the power and convenience of WebRTC.
Cloud resources, although available in abundance, are inherently volatile. For transactional computing, like ERP and most enterprise software, this is a challenge as transactional integrity and data fidelity is paramount – making it a challenge to create cloud native applications while relying on RDBMS. In his session at 21st Cloud Expo, Claus Jepsen, Chief Architect and Head of Innovation Labs at Unit4, will explore that in order to create distributed and scalable solutions ensuring high availa...
For financial firms, the cloud is going to increasingly become a crucial part of dealing with customers over the next five years and beyond, particularly with the growing use and acceptance of virtual currencies. There are new data storage paradigms on the horizon that will deliver secure solutions for storing and moving sensitive financial data around the world without touching terrestrial networks. In his session at 20th Cloud Expo, Cliff Beek, President of Cloud Constellation Corporation, d...
Internet-of-Things discussions can end up either going down the consumer gadget rabbit hole or focused on the sort of data logging that industrial manufacturers have been doing forever. However, in fact, companies today are already using IoT data both to optimize their operational technology and to improve the experience of customer interactions in novel ways. In his session at @ThingsExpo, Gordon Haff, Red Hat Technology Evangelist, shared examples from a wide range of industries – including en...
In IT, we sometimes coin terms for things before we know exactly what they are and how they’ll be used. The resulting terms may capture a common set of aspirations and goals – as “cloud” did broadly for on-demand, self-service, and flexible computing. But such a term can also lump together diverse and even competing practices, technologies, and priorities to the point where important distinctions are glossed over and lost.
In his session at @DevOpsSummit at 20th Cloud Expo, Kelly Looney, director of DevOps consulting for Skytap, showed how an incremental approach to introducing containers into complex, distributed applications results in modernization with less risk and more reward. He also shared the story of how Skytap used Docker to get out of the business of managing infrastructure, and into the business of delivering innovation and business value. Attendees learned how up-front planning allows for a clean sep...
Most companies are adopting or evaluating container technology - Docker in particular - to speed up application deployment, drive down cost, ease management and make application delivery more flexible overall. As with most new architectures, this dream takes a lot of work to become a reality. Even when you do get your application componentized enough and packaged properly, there are still challenges for DevOps teams to making the shift to continuous delivery and achieving that reduction in cost ...