Sequoia Capital backs Q-Ctrl, the Australian quantum computing start-up

The investors behind a who's who of tech giants ranging from @Apple and @Airbnb to @Yahoo and @YouTube are pouring money into a small Australian #quantumcomputing company, cementing Australia's position as a leader in the technology that is expected to revolutionise the 21st century. Sequoia Capital, the Silicon Valley venture capitalists that also backed @Google, Instagram and @PayPal, are now backing @Q-Ctrl, a quantum computing software company based at the @University of Sydney. Q-Ctrl's software, developed by Professor Michael Biercuk at the University of Sydney Quantum Control Laboratory, is designed to help solve what has emerged as one of the biggest problems slowing down the development of a useful quantum computer: how to keep the delicate, atom-scale data bits, known as quantum bits or "qubits", stable long enough for them to be used for computations. To give quantum computers an advantage over classical computers, qubits have to exist in a state known as "superposition", where they represent 0 and 1 at the same time, and where they can be used to quickly make calculations that are either unfeasibly slow, or completely impossible, with the classical data bits now used the world over, which can represent either 1 or 0 but cannot be both at once.

https://www.afr.com/technology/sequoia-capital-backs-australian-quantum-computing-startup-qctrl-20180706-h12cu8

Yahoo is giving a critical piece of internal technology to the world -- just like it did with Hadoop

Yahoo is open-sourcing an internal tool called #Vespa, which it uses for content recommendations, ad serving, and executing certain searches. Vespa is arguably #Yahoo 's biggest open-source software release since #Hadoop in 2009, which formed the basis for two now-public companies, #Hortonworks and #Cloudera. Companies like #Amazon, #Facebook, and #Google could find it useful.

Oath, the #Verizon-owned parent company of Yahoo, is releasing for free some of its most important internal software, which the company has long used to make recommendations, target ads and execute searches.

The Vespa software solves a common but surprisingly difficult problem: quickly figuring out what to show a user in response to input, like when they type text into a box. Oath uses it in around 150 applications, including Flickr, Yahoo Mail and the main Yahoo search engine (specifically for components like entities, local results, images and answers to questions). It handles 3 billion native ad requests every day.

"The typical case is you don't know what you want to serve, but you have 20 billion pictures and you want to find the right ones," Jon Bratseth, a distinguished architect at Yahoo who led Vespa's development, told CNBC in an interview.

Vespa, which is now live on GitHub with an Apache 2.0 open-source license, can easily be added to different applications, making it suitable for use at big companies like Amazon, Facebook and Google that need to do different kinds of processing on different sets of data.

The release is the most important for Yahoo since it open-sourced the code for the Hadoop big data software in 2006. Hadoop has since come to be at the center of two public companies, Cloudera and Yahoo spin-off Hortonworks. Today people at lots of companies can contribute to technology that's still widely used at Yahoo, and build their own systems using Hadoop.

How Yahoo built it

Big tech companies regularly open-source their software. But if there's powerful software at the heart of a company's biggest revenue centers, it can take a while to come out into the open, and Vespa is no different.

Vespa dates back to the early 2000s. Yahoo already had web search technology, first through a partnership with Google and later through its 2002 Inktomi acquisition. What Yahoo didn't have was technology for delivering search results and recommendations on content that falls outside traditional web search results.

In 2003 Yahoo acquired Overture, which included its partner AltaVista as well as a lesser known search engine called AllTheWeb.com. After the deal, the roughly 30 AllTheWeb people were given a year to build software that could perform certain functions quickly before web pages were shown to end users. The system also needed to be easy to set up, run and tweak, so that it could be applied to a variety of applications without much trouble.

In around 2005, the AllTheWeb team worked with Yahoo's shopping team to adopt the new system. It required less management time, freeing up staffers to build new features.

"After that, we had a proven use case -- and that was a complicated one," Bratseth said. "More and more teams in Yahoo started using our system by themselves, because it made business sense. They would offload a lot of the problems they had to take care of themselves."

So Bratseth's team started expanding the powers of Vespa. They made it capable of handling input other than users' strings of text; over time it could also personalize content based on what users had clicked on in the past, which is valuable in cases when users haven't typed in anything. They also changed Vespa so that it could take direction from machine-learning algorithms.

https://www.cnbc.com/2017/09/26/yahoo-open-sources-vespa-for-content-recommendations.html

Yahoo’s Massive Hadoop Scale on Display at Dataworks Summit

#Yahoo put its massive #Hadoop investment on display this week at #Dataworks Summit, the semi-annual big data conference that it co-hosts with #Hortonworks. While Hadoop is no longer the conference headliner that it once was, the platform is still critical for the daily operations of Yahoo, which officially became part of #Verizon Communications this week when the $4.5 billion acquisition finally closed. With 120,000 servers and 800 PB of in storage, few companies have the computing scale of Yahoo. And as the birthplace of this distributed computing platform called Apache Hadoop, it’s worth keeping an eye on what Yahoo is doing with its collection of big data tech. Sumeet Singh, the senior director of cloud and big data platforms at Yahoo, took to the Dataworks Summit stage on Wednesday to describe how the technological makeup of Yahoo’s massive cloud platform has evolved over the years. For starters, the company is moving solidly away from #MapReduce. Over the past 17 months, Tez has replaced MapReduce as the underlying engine for many of the batch-oriented #Pig and #Hive workloads that Yahoo relies on to serve its 1 billion monthly users. Today, 70% of the Hadoop workloads and Yahoo run under Tez, according to Singh. Use of Apache Spark has also grown, but not nearly as quickly as Tez, he says. Singh referred to this switch from MapReduce to Tez and Spark as “compute shaping.” “What compute shaping does, it allows us to make better use of the platform,” he says. “This is fantastic for the company and our customers because they can make better use of the capacity.”

https://www.datanami.com/2017/06/16/yahoos-massive-hadoop-scale-display-dataworks-summit/

Verizon closes $4.5B acquisition of Yahoo, Marissa Mayer resigns [Memo]

It’s now official. After #Yahoo shareholder approval last week, #Verizon today announced that it has finally closed its acquisition of Yahoo, which it plans to combine with its #AOL assets into a subsidiary called #Oath, covering some 50 media brands (including TechCrunch) and 1 billion people globally. It will be led by Tim Armstrong, who was the CEO of AOL before this. As expected, Marissa Mayer, who had been the CEO of Yahoo and recently received a $23 million ‘golden parachute’ for her work there, has resigned. “Given the inherent changes to Marissa Mayer’s role with Yahoo resulting from the closing of the transaction, Mayer has chosen to resign from Yahoo. Verizon wishes Mayer well in her future endeavors,” Verizon said in a statement. You can find Marissa in her own words here on Tumblr. TLDR: It’s a long list of the achievements made with her at the helm these last five years, and — alas — you will only read of the struggles that Yahoo went through between the lines. The deal, nevertheless, brings to a close the independent life of one of the oldest and most iconic internet brands, arguably the one that led and set the pace for search — the cornerstone of doing business on the spaghetti-like internet — at least until Google came along and surpassed Yahoo many times over, and led the company into a number of disastrous and costly attempts to redefine itself, ultimately culminating in the sale we have here today. The sale of Yahoo is another sign of the massive consolidation that continues to happen in the world of online media and content, as large companies look to bring together multiple audiences for economies of scale to build out stronger advertising businesses in competition with the likes of Google and Facebook. “The close of this transaction represents a critical step in growing the global scale needed for our digital media company,” said Marni Walden, Verizon president of Media and Telematics (which will include Oath), in a statement. “The combined set of assets across Verizon and Oath, from VR to AI, 5G to IoT, from content partnerships to originals, will create exciting new ways to captivate audiences across the globe.” Carriers have been an especially interesting player in this regard, as they are looking to offset declines in their legacy businesses. But don’t cry for Verizon just yet: the company employs 161,000 people and made $126 billion in revenues in 2016, with 113.9 million retail connections in its mobile business. As we wrote last week, there will be cuts of around 15 percent of all staff associated with the acquisition of Yahoo and merger with AOL, around areas like operations and sales and marketing. Today, no word about that in the official announcement although we are asking about this. Also not specified is who else is departing along with Mayer. As we reported last week, Adam Cahan, who had been an SVP at Yahoo very close to Mayer, was also on his way out, as was Bob Lord, the CISO who was at the head of Yahoo’s security operations when its massive breaches were revealed (although he was not there not at the time that they were taking place). That breach resulted in Verizon knocking off several hundred million dollars from its original offer price for the company. A spokesperson for AOL/Oath declined to comment on specific departures, and provided the following statement about the other redundancies, in line with previous statements: “Oath’s strategy is to lead the global brand space. With access to over 1B consumers upon close, we will be positioned to drive one of the most important platforms in the consumer brand space. Consistent with what we have said since the deal was announced, we will be aligning our global organization to the strategy.” In the meantime, unsurprisingly, David Filo, Eddy Hartenstein, Richard Hill, Marissa Mayer, Jane Shaw, Jeffrey Smith and Maynard Webb Jr. have already resigned from Yahoo’s board. “We’re building the future of brands using powerful technology, trusted content and differentiated data. We have dominating consumer brands in news, sports, finance, tech, and entertainment and lifestyle coupled with our market leading advertising technology platforms,” Armstrong said in a statement. “Now that the deal is closed, we are excited to set our focus on being the best company for consumer media, and the best partner to our advertising, content and publisher partners.” This will include not just media brands but ad tech underpinnning how to leverage these audiences. In this case, the focus in on ONE by AOL and its BrightRoll technology covering mobile, video, search, native and programmatic ads.

https://techcrunch.com/2017/06/13/verizon-closes-4-5b-acquisition-of-yahoo-marissa-mayer-resigns-memo/

The Elephant In The Room With Hadoop: It Offers Rich Technology With Slimmer-Than-Expected Margins

With the strong growth over the past 10 to 15 years of #AmazonWebServices, #Microsoft #Azure, #Google and #Yahoo, data center technologies have advanced rapidly from their enterprise roots as IT professionals work to serve the needs of these web services providers. The sheer scale required by just one of these providers dwarfs even the largest Enterprise infrastructures. Notably, as well, with the emergence of Cloud computing, many Enterprises operate hybrid infrastructures, with business units maintaining infrastructures in both their own Private and Public Clouds such as AWS or Azure. Technologies developed to suit the needs of one increasingly are being deployed in the other, especially with the proliferation of #BigData.

Surely the most whimsically named of these technologies is #Hadoop, an #OpenSource software framework used to manage large clusters of servers. It is a collection of technologies developed over ten years ago by engineers at Yahoo, including Sean Suchter and Doug Cutting, the latter of whom named the framework after his son's toy elephant. The framework runs on clusters of servers running the Apache operating system and its development is managed by the Apache Software Foundation. To boot, a cheerful yellow elephant has been adopted as its logo.  Like all Open Source software, the technologies are free to be adopted and developed by third parties within the foundation framework, hence the term "open".  Since no license fee is collected, no revenue is generated for what is essentially a non-profit entity.

Yet software is typically a very profitable business. Once developed, software license sales have a low cost of sales and gross profit margins can be as high as 85%. Operating leverage is very high, moreover, and operating profitability scales rapidly with size. In fact, Oracle reports no Cost of Sales and its non-GAAP operating margin in the February quarter was a robust 32%. That said, Hadoop is Open Source software and licensed by the Foundation through its distributors, who only charge for subscription support and professional services. Other notable examples of Open Source Software are Java and Linux.We will return this below.

https://www.forbes.com/sites/johnsonpierr/2017/05/19/the-elephant-in-the-room-with-hadoop-it-offers-rich-technology-with-slimmer-than-expected-margins/?c=0&s=MarketMoves

That Giant Sucking Sound? Hadoop Moving Into The Cloud

#Hadoop was born in the cloud, as a #bigdata project designed to take advantage of #Yahoo ’s infrastructure, based on a paper from #Google about the #mapreduce algorithm. It was never originally designed for on prem enterprise deployment. I recently wrote that some of the issues with Hadoop adoption are cultural, but management overheads are another problem – setting up clusters, capacity planning, maintaining and updating versions etc. Keeping cluster running, the basic care and feeding that any distributed system requires. Another management issue is the sheer pace of innovation in open source big data tooling. Hadoop is great for counting and sorting in batch mode and Hadoop Data File System (HDFS) is a powerful data reservoir, but then what? The query infrastructure is still immature, and targeted at highly skilled and expensive data scientists with language skills rather than common or garden SQL tooling. As data workloads increasingly became stream-based, Spark took off. Then we needed a message bus, and Kafka emerged as the platform of choice. But how is all of this stuff supposed to fit together? Enterprises, in general, don’t want to be systems integrators (except of course, the ones that do) and prefer to outsource the packaging of technology to third parties. Cloudera, Hortonworks, Map/R were founded as Hadoop distribution providers, and have responded to the rate of change issue but broadening their story and embracing Spark and Kafka, positioning themselves as broad next generation data platforms But many early deployments were on prem, which meant management overheads remained, especially in a world where new software versions off all of the pieces of the stack are emerging at a furious pace. Updating on prem software sucks. Even in the cloud though it promises elastic scalability, capacity planning is an issue – what happens when your Hadoop cluster grows out of the sizing you have set up on AWS Cloud? Hadoop and associated tooling carries a fairly significant management overhead. While the distribution players can mitigate these issues to some extent, the alternative is managed serviced from AWS, Azure and Google Cloud Platform (GCP). If lighthouse customers is anything to go by, Google may have found a sweet spot in picking up customers that are fed up with with running Hadoop, and are looking for an integrated set of offerings that don’t carry a management overhead. Google has its ducks in a row from a packaging perspective. One of the first major GCP wins for its Big Data services was Spotify, which said loud and clear it was willing to trade openness for convenience and extra capability. HSBC spent tens of millions of pounds standing up its own Hadoop infrastructure for anti-money laundering (AML) but was disappointed with the results. It has now migrated to GCP for AML, and is beginning to migrate other workloads there, such as finance liquidity reporting. The strategy is Cloud First and GCP is really well positioned there. Ocado is an online grocery delivery platform, which also offers third party digital and fulfilment services. It’s a classic platform play and has gone all in on Google Cloud for data. Interestingly it would be even more aggressive about adopting Google infrastructure were it not for corporate restrictions on adopting beta versions.

https://www.enterpriseirregulars.com/115048/giant-sucking-sound-hadoop-moving-cloud/

Hadoop fails to live up to the promise and the hypeThe cost and complexity of

#Hadoop, the #opensource #bigdata framework first developed at #Yahoo for analyzing large data sets, is a total failure that costs too much and is too much of a headache to implement, say people in the field. In a lengthy and in-depth piece on #Datanami, big data experts describe Hadoop as too primitive for any kind of complex processing work or interactive, user-facing applications. At best, it's a batch process job, which is how Hadoop started out. It doesn't seem to have grown beyond it.

http://www.networkworld.com/article/3185559/storage/hadoop-fails-to-live-up-to-the-promise-and-the-hype.html

How Yahoo’s Internal Hadoop Cluster Does Double-Duty on Deep Learning

Five years ago, many bleeding edge IT shops had either implemented a #Hadoop cluster for production use or at least had a cluster set aside to explore the mysteries of #MapReduce and the #HDFS storage system. While it is not clear all these years later how many ultra-scale production Hadoop deployments there are in earnest (something we are analyzing for a later in-depth piece), those same shops are likely on top trying to exploit the next big thing in the datacenter—machine learning, or for the more intrepid, deep learning. For those that were able to get large-scale Hadoop clusters into production and who now enjoy a level of productivity on those systems, integrating deep learning and machine learning presents a challenge—at least if that workload is not being moved to an entirely different cluster for the deep learning workload. How can Caffe and TensorFlow integrate with existing data in HDFS on the same cluster? It turns out, it is quite a bit easier, even with the addition of beefy GPU-enabled nodes to handle some of the training part of the deep learning workflow. Work on this integration of deep learning and Hadoop comes from the least surprising quarters—Yahoo, the home of Hadoop and MapReduce over a decade ago. Yahoo’s main internal cluster for research, user data, production workloads across its many brands and services (search, ad delivery, Flickr, email), and now deep learning is all based on a mature Hadoop-centered stack. Over time, teams at #Yahoo have integrated the many cousins of #Hadoop; #Spark, #Tez, and more, but they are now looking to capture trends in open source that float away from the #Apache base for large-scale analytics they’ve cultivated over the years.
https://www.nextplatform.com/2017/02/16/yahoos-internal-hadoop-cluster-double-duty-deep-learning/

Yahoo & Microsoft open source data analytics tools for Spark & Graph Engine

#Yahoo and #Microsoft have open sourced two data analytics tools that can help businesses to become more data-driven. Yahoo, has decided to open source the #TensorFlowOnSpark software that was created to make #Google ’s #TensorFlow open source framework compatible with the data sets that sit inside #Spark clusters. To grossly simplify this, TensorFlow is an open source software library that users can tap in to for numerical computation using data flow graphs. The company said: “TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from deep learning framework TensorFlow and big-data frameworks Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers.” It’s easy to forget that Yahoo has some brilliant technical minds working at the company, what will all the issues regarding the data breaches at the Internet side of the business, but the company has history in the big data world.
http://www.cbronline.com/news/big-data/analytics/yahoo-microsoft-open-source-data-analytics-tools-spark-graph-engine/

News Bits: DDN, IBM, VMware, Crucial, Nasuni, Virtual Instruments, & More

This week’s #NewsBits we look at a number of small announcements, small in terms of the content not the impact they have. #IBM and #DDN work together to provide #Yahoo!Japan a 50TB/day transfer rate with a new active archive system. #VirtualInstruments announced #LoadDynamiXEnterprise version 5.2. #VMware has made its integrated containers generally available. #Crucial upgrades its #DDR4 sever memory to 2666MT/s. #IBM announced a 12-month free trial of its #CloudObjectStorage solution. #Nasuni raises #25 million in new round of financing. And #Datera partners with #CoreOS to accelerate stateful #Kubernetes for on-prem clouds.

http://www.storagereview.com/news_bits_ddn_ibm_vmware_crucial_nasuni_virtual_instruments_more

Hadoop Summit Expands to Address Growing Data Ecosystem

SANTA CLARA, Calif., Dec. 12, 2016 /PRNewswire/ -- Hosts #Hortonworks® (NASDAQ: HDP) and #Yahoo ! today announced the expansion of #HadoopSummit to include #DataWorksSummit to meet the demands of a growing and accelerating data ecosystem. DataWorks Summit and Hadoop Summit will spark conversation around today's modern data applications and the importance of a connected data architecture, of which #ApacheHadoop and related technologies play integral roles. Starting with the 2017 conference in Munich, Germany on April 5-6, DataWorks Summit and Hadoop Summit will bring partners and customers together to discuss business transformations fueled by data and customer innovation. "As customers look to the Internet of Things, cloud and modern data applications to fuel business transformation, we saw an opportunity to expand Hadoop Summit to also include the those growing communities," said Matt Morgan, senior vice president of marketing, Hortonworks. "DataWorks Summit and Hadoop Summit offers a unique opportunity for customers and partners to interact with thought leaders, Apache Committers, industry luminaries and thousands of their peers and learn from the best minds across the open source community." For the first time, the event's Community Showcase will have specific areas that reflect the broader trends and technologies in the ecosystem: Apache Hadoop Zone IoT & Streaming Zone Cloud & Operations Zone Apache Spark & Data Science Zone DataWorks Summit and Hadoop Summit is a unique event because all technical sessions are voted on and vetted by the community. Every session is chosen by a track committee made up from experts across many organizations. In addition, each business session is led by industry experts and business leaders who share real use cases, success stories, and best practices.
http://www.prnewswire.com/news-releases/hadoop-summit-expands-to-address-growing-data-ecosystem-300376211.html

Blockchains for Big Data

#Bigdata arose in the early and mid 2000s to meet internet-scale computation needs: #ZooKeeper at #Yahoo, #BigTable and #MapReduce at #Google, #Cassandra at #Facebook; and so on. Then came open source projects like #Hadoop File System ( #HDFS ), Hadoop MapReduce, Cassandra, and more. By the late 2000s and early 2010s, startups like #MongoDB, #Cloudera, and #DataStax had created businesses to transform the open source successes into enterprise-grade offerings. Now, big data technology is quietly transforming every enterprise backend on the planet. For example, in many places “data warehouses” of relational databases are getting replaced by “data lakes” running big data software. More than $100B annually is going towards big iron compute clusters, the software on top, and the services to keep it all running smoothly. Big Data Challenges But big data has its challenges, which include control, data authenticity and monetization. First, who controls the infrastructure when there are multiple actors involved? For example: If you’re a multinational enterprise, how do you share data around the planet? If you have multiple copies, how do you know which one is the most up-to-date? How do you reconcile a different system administrator role at each regional office? If you’re an industry consortium, how to share control of the ecosystem infrastructure among the companies in your consortium? This is especially hard if those companies are competitors! Why can’t there be data just “out there” as a single shared source of truth that no one on the planet owns or controls, per se? Rather, data would be a public utility like electricity or the internet itself. Second, how well can you trust the data? For example: If you generate the data yourself, how do you prove you were the originator? If you get data from others, how do you know it was truly them? What about crashes and malicious behavior? Machines crash, glitches happen, bits flip. Zombie IoT toasters might be inputting garbage. So after all your fancy Spark calculations, is it still just garbage out? Finally, how do you monetize the data? For example: How do you transfer the rights of the data, or buy rights from others? There’s a long standing dream of a universal data marketplace; how? A New Tool For Big Data: Blockchain Technology The recent surge in blockchain technology was sparked by Bitcoin. Technically, all blockchains are simply databases, but databases with “blue ocean” benefits: decentralized / shared control, immutability / audit trails, and native assets / exchanges. By modern database standards, traditional blockchains have terrible scalability and don’t even have query languages; nonetheless, the blue ocean benefits were enough to capture the imagination of the globe. Better yet, more recent technology — the BigchainDB blockchain database— combines the benefits of distributed databases (scale, queryability) and blockchains (decentralized, immutable / audit trails, assets / exchanges). This new blockchain database technology has the scalability needed in big data environments, by building on top of best-in-class distributed databases like MongoDB. This unlocks the potential for highly interesting applications in big data: shared control of infrastructure, audit trails on data, and the possibility for a universal data exchange. Let’s explore both in detail. Shared Control of Big Data Infrastructure Summary. Being a blockchain database means that control of the database infrastructure is shared across the entities, whether within-enterprise, within a consortium, or across the planet. How. A big data blockchain database like BigchainDB is decentralized, which means that its control can be shared

http://bravenewcoin.com/news/blockchains-for-big-data/

Hadoop Introduction – A Comprehensive Guide for Beginners

This tutorial provides thorough introduction of #Hadoop. The tutorial covers what is Hadoop, what is the need of Hadoop, why hadoop is most popular, Hadoop Architecture, data flow, Hadoop daemons, different flavours, introduction of Hadoop componenets like hdfs, #MapReduce, #Yarn, etc. Hadoop is an open source tool from the #ASF – #Apache Software Foundation. Open source project means it is freely available and even its source code can be changed as per the requirements. If certain functionality does not fulfill your requirement, you can change it according to your need. Most of Hadoop code is written by #Yahoo, #IBM, #Facebook, #Cloudera.

Read more at Data Flair

https://www.linux.com/news/hadoop-introduction-comprehensive-guide-beginners

Activist investor Starboard Buys a Stake in Hewlett Packard Enterprise

There was #Yahoo. There was #Depomed. There was #Marvell Technology. And now, with a new investment in Hewlett Packard Enterprise ( #HPE ), activist investor #StarboardValueFund appears to be going for a grand slam of cage-rattling among Bay Area businesses this year. According to a regulatory filing on Monday, New York-based Starboard has acquired a $124.7 million stake in HPE. It remains to be seen if Starboard, a hedge fund headed up by investor Jeffrey Smith, will reach out to HPE Chief Executive Meg Whitman in an effort to increase its influence at the enterprise -technology company that was created when Hewlett-Packard split in two in 2015. Neither Starboard nor HPE returned requests for comment on the investment. It's not uncommon for institutional investors and fund managers to buy large amounts of stock in publicly traded companies, but Starboard is another animal. Starboard is known for buying up stakes in companies that it views as being improperly managed or undervalued. It then launches efforts to shake up those organizations, often by seeking to add several of its own nominees to those companies' boards of directors. Starboard is no stranger to the CEOs around the Bay Area. Already this year, Starboard has used its stock ownership and activist philosophy to grab seats on the boards of chipmaker Marvell Technology, which has its U.S. headquarters in Santa Clara, and pharmaceutical company Depomed, of Newark. Its most high-profile attack came against Yahoo when, earlier this year, Starboard said it would submit a slate of directors to replace Yahoo's entire board, including CEO Marissa Mayer. Starboard and Yahoo reached a sort of a truce in April, when Yahoo added four of Starboard's nominees to its board of directors. Yahoo is now in the process of being sold to Verizon Communications.

http://www.cio-today.com/article/index.php?story_id=100006J0HHNS

Verizon Says Yahoo Hack Could Reopen $4.8 Billion Deal Talks

SAN FRANCISCO — #Verizon Communications may seek to renegotiate its $4.8 billion purchase of #Yahoo ’s operating business, dealing another blow to the struggling internet company. Verizon’s top lawyer said on Thursday that his company thought that the hacking of 500 million Yahoo email accounts in 2014 — disclosed last month, well after the deal was announced — had materially diminished the value of Yahoo, potentially allowing Verizon to reopen the sale discussions. “I think we have a reasonable basis to believe right now that the impact is material, and we’re looking to Yahoo to demonstrate to us the full impact,” Craig Silliman, Verizon’s general counsel, told reporters in Washington. “If they believe that it’s not, then they’ll need to show us that.” The data breach, most likely the largest ever at a private company, is still under investigation by the companies and the Federal Bureau of Investigation. F.B.I. officials have confirmed that the Yahoo breach has the hallmarks of a state-sponsored attack, but they also say it is too early to say which country was behind it, according to two people who with knowledge of the investigation who spoke on the condition of anonymity. In a statement on Thursday, Yahoo said, “We are confident in Yahoo’s value and we continue to work towards integration with Verizon.” The transaction is expected to close by early next year.

http://mobile.nytimes.com/2016/10/14/business/dealbook/verizon-says-yahoo-hack-could-reopen-4-8-billion-deal-talks.html?_r=0&referer=https://www.google.com/

AOL is losing its top global-sales exec ahead of the Yahoo deal

#AOL is losing its top global-sales exec in the middle of its deal to merge its operations with #Yahoo. #Verizon agreed to buy Yahoo for $4.68 billion earlier this year. Since then, their executives, including AOL’s Tim Armstrong, have been working on coordinating the inevitable integration. Jim Norton’s departure comes as AOL and Verizon are trying to figure out the best organization to create after it completes its deal with Yahoo, which is expected to happen later this year or early next year. Sources say that there are plans to split AOL into two units, one that will focus on media and advertising and the other on platforms and tech. Presumably, the strategy is to fit Yahoo’s unit into that structure. There is a possible glitch due to recent revelations about a data breach at Yahoo; because of the breach, Verizon and Yahoo are discussing potential liabilities that may impact terms of the deal. But executives at AOL and Verizon are proceeding as if it will be happening at this time. Norton’s exit is yet another wrench in what has become a complex deal. He is a key player at AOL as the company’s global head of media sales. He came there in 2011 from Google, where Tim Armstrong, now CEO of AOL, was its top sales exec. He is leaving for Condé Nast, but it’s not clear what his role there will be. Presumably, it’ll be a top sales position.
http://www.recode.net/2016/10/10/13227166/aol-yahoo-jim-norton-conde-nast

Is this the age of Big OLAP?

There was a time when analytics was synonymous with #BI, and BI was synonymous with #OLAP -- Online Analytical Processing. The term was meant to contrast with the more common Online Transaction Processing (OLTP), and involved the creation of multi-dimensional "cubes" rather than 2-dimensional tables. Each dimension is a different category with which to perform drill-down analyses on numerical data, known as measures. Now that you've had your BI 101 crash course, look around at numerous analytics products like Tableau, and you'll see the paradigm of dimensions and measures is alive and well. OLAP never died, even if its underlying technologies morphed a bit. The justice of scale What has dogged OLAP, though, is its scalability. Most OLAP servers run on single, albeit beefy, servers, which limits the parallelism that can be achieved and therefore imposes de facto limits on data volumes. Customers who hit these scalability ceilings may contemplate using Big Data technologies, like Hadoop and Spark, but those tend not to employ the dimensional paradigm to which OLAP users are accustomed. What to do? Well, a few vendors have decided to take Hadoop and Spark, and leverage them as platforms on which big OLAP cubes can be run and built. The vendors, namely AtScale, Kyvos Insights and Arcadia Data, have looked at Big Data adoption patterns in some enterprises, and seen that momentum has stalled. Their approach has been to let people in those enterprises work in the OLAP environments they are comfortable with and, at the same time, make use of their #Hadoop clusters. AtScale's CEO, David Mariani, was the person behind a couple of the biggest #Microsoft OLAP projects (at #Yahoo and #Klout). And while he was able to do big things with Microsoft's OLAP platform, SQL Server Analysis Services (SSAS), he definitely hit up against scalability limits, including cube re-processing times of as much as a week. His motivation for creating a more resilient OLAP platform was pretty clear, so he formed #AtScale.

http://www.zdnet.com/article/is-this-the-age-of-big-olap/

SAP buying former Yahoo CTO's Big Data startup for more than $125M

#SAP is reportedly buying cloud-based #BigData software startup #Altiscale for more than $125 million. Venturebeat cited an unnamed source in a story on Thursday that said a deal is likely to be announced in the next few weeks. #hadoop

http://www.bizjournals.com/sanjose/blog/techflash/2016/08/sap-buying-former-yahoo-ctos-big-data-startup-for.html

A Former Yahoo CTO Just Became CEO Of This Big Data Startup

@AshfaqMunshi joins other ex- #Yahoo employees, who created big data startup #Pepperdata. A former CTO of Yahoo and long-time Silicon Valley veteran is taking over as CEO of big data startup Pepperdata. Ashfaq Munshi, who worked at Yahoo for a little under a year right before Marissa Mayer became CEO, succeeds Pepperdata co-founder Sean Suchter, who will become the startup’s CTO. Suchter and Pepperdata co-founder Chad Carson both held management positions at #Microsoft MSFT -0.31% and Yahoo YHOO 1.76% before creating the startup in 2012. At Yahoo, Suchter helped the company’s search business unit successfully use the open-source #Hadoop big data framework not just for testing or research projects, but also in production.
http://fortune.com/2016/08/09/yahoo-cto-ceo-data-pepperdata/

Verizon eyes automotive technology market, could spur other deals

#Verizon Communications Inc's recent purchases of two vehicle tracking firms could spark more deals as the No. 1 wireless provider and rival #AT&T see fleet management as a source of growth, analysts said. Faced with a saturated wireless market, several telecom companies are looking beyond their main phone business for ways to extract more value from existing networks. Just last month, Verizon bought #Yahoo for $4.8 billion, diving into digital media and advertising. But Verizon also recently acquired privately held connected-vehicle technology firm Telogis for an undisclosed sum and said it would buy GPS vehicle tracking company #Fleetmatics Group Plc for $2.4 billion. Telecom providers are moving towards acquiring "eyeballs or a fleet of people" that can use applications built on top of the wireless network, said Richard McBee, chief executive officer of Canadian communications technology company Mitel Networks Corp. The fleet and mobile workforce management business connects fleet vehicles to the wireless network and collects data, like driver behavior, to manage vehicles and workers. The business delivers a source of recurring subscription-based revenue from clients such as large logistics companies and local delivery services.

http://mobile.reuters.com/article/idUSKCN10K23Q