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UPDATE – Quick Take: Is Oracle Buying Tiktok? (Hint: It’s all about the cloud)

Last Updated January 20th, 2021

(Update: As of January 20th, with the presidential inauguration of Joe Biden, it seems unlikely that the Biden administration will continue the pursuit of the US ban on Tiktok. This follows U.S. District Court Judge Carl Nichols Dec. 7 ruling that the Commerce Department had “likely overstepped” its authority in placing the ban. An earlier injunction on shutting down Tiktok services on October 30th in the United States Court of Appeals for the Third Circuit by Judge Wendy Beetlestone is currently scheduled to be appealed in February 2021.)

Key Takeaway: Master tactician Larry Ellison gains a feather in the Oracle Cloud by playing the long game and positioning Tiktok as a significant Oracle Cloud customer. Well played, Mr. Ellison.

As if 2020 hasn’t been weird enough, many of us are finding out that enterprise stalwart Oracle is apparently going to purchase Gen Z (born after 1995) and Gen Alpha (born 2010 or later) social media darling Tiktok.

What? Is this actually happening?

Well, not quite. But to explain, first we need to look at the context.

Last month, President Trump created an executive order to ban Tiktok in the United States based on security and censorship issues. This move was seen both as a move against the Chinese economy and to protect global social media platforms based in the United States such as Facebook and Twitter.

In response, a number of potential suitors showed up with either bids or proposals to support Tiktok in the United States. Microsoft showed interest in purchasing Tiktok to support its Azure cloud and gain a massive source of video content that would be useful across Microsoft’s marketing (Bing), gaming (XBox, Minecraft), augmented reality (Hololens), and artificial intelligence (Azure AI) businesses. And at one point, retail giant Walmart was associated with this bid, perhaps in an attempt to fend off Amazon in this digital path. But this bid was shut down was rejected on September 13.

Oracle came in after Microsoft, showing interest in Tiktok. At the time, there was massive confusion from the market at large on why Oracle would be interested. But, as someone who has written about the tight relationship between social technologies and the cloud for many years, my immediate thought was that it’s all about the cloud.

Oracle has been forcefully marketing Oracle Cloud Infrastructure as an enterprise solution after making significant investments to improve connectivity and usability. These recent changes have led to significant logo wins including Zoom and 8×8, both of which chose Oracle for its performance and 80% savings on outbound network traffic. The cost of connectivity has traditionally been a weak point for leading cloud providers, both due to a lack of focus on networking and because cloud vendors have wanted to gate data within their own platform and have little to no incentive to make inter-cloud transfers and migrations cheaper and easier. But Oracle’s current market position combined with its prior investments in high performance computing and network performance means that it makes good business sense for Oracle to be the most efficient cloud on a per-node and bandwidth perspective and to attack where other cloud vendors are weak.

Social media and communications vendors are massive cloud customers, in their own right. Pinterest has a 6 year, $750 million commitment with Amazon Web Services and is easily on pace to spend far more. Lyft has its own $300 million commitment wth AWS. And Citrix has a $1 billion commitment with its cloud vendor of choice, presumably Microsoft Azure. The cloud contract sizes of large and dynamic social and video-centric vendors is enormous. Every cloud provider would be glad to support the likes of Tiktok as a customer or potentially even as a massive operations writeoff that would be countered by the billions of dollars in revenue Tiktok provides.

And, of course, Tiktok creates a massive amount of data. Similar to Microsoft’s interest in Tiktok, Oracle obviously has both expertise and a large business focused on the storage and analysis of data. Managing Tiktok content, workloads, and infrastructure would provide Oracle with technical insights to video creation trends and management that no other company other than perhaps Alphabet’s Youtube could provide. Over the past couple of years, Oracle has put a lot of effort both into database automation and cloud administration with its Gen2 offering.

In addition to bolstering Oracle’s cloud, Tiktok also could make sense as a tie-in to Oracle’s Marketing Cloud. At a time when large marketing suites are struggling to support new platforms such as Tiktok, what better way to develop support than to own or to access the underlying technology? But wait, does Oracle have access to Tiktok’s code and algorithms?

Apparently not. Current stories suggest that Oracle will be the hosting partner or “Trusted Technology Provider” for Tiktok America while Tiktok parent company ByteDance still maintains a majority ownership of the company. It looks like Oracle has positioned itself to be the cloud provider for a massive social media platform, as the United States alone has over 100 million active users on Tiktok. And the speculation behind Microsoft’s rejected bid is that Microsoft sought to purchase the source code and algorithms of Tiktok, which ByteDance refused to provide.

So, the net-net appears to be that in response to Trump’s Executive Order, Oracle will gain an anchor client for Oracle Cloud Infrastructure while making some investment into the new Tiktok US organzation. Oracle’s reputation for security and tight US government relations are expected to paper over any current concerns about data sovreignty and governance, such as Chinese access to US user data. Current Tiktok investors, such as General Atlantic and Sequoia Capital, may also have stakes in the new US company. This activity effectively puts more money into a Chinese company. Most importantly, this action will allow Tiktok to remain operational in the United States after September 20th, the original due date of the executive order.

Congratulations to Oracle and Larry Ellison on a game well played.

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From BI to AI: The Evolutionary Path of Enterprise Analytics

As we progress along the road of this pandemic-driven recession, CIOs and IT departments need to keep a clear-eyed view of the future and the tasks that we are held to manage. Because even as we deal with all the challenges of remote work, distributed decisions, and uncertain economic environments, we are also held to the challenges of supporting future business needs and supporting the next generation of technology, which continues to be created and launched. 

This means that we need to follow the path of COVID IT

If you’ve followed the stages and actions we recommended in our webinar series or at our Technology Expense Management Expo, you’ve passed through the stage of pure survival, securing remote work, and auditing your environment. Now, we are at Stage 4, which is to gather best practices, celebrate successes, and train employees on the New Normal.

A key aspect of Stage 4 and Stage 5 is the use of data and analytics to support better decision making, improved forecasting, more nuanced automation, and more accurate models and workflows to make sense of complex business phenomena as your organization continues to move from BI (Business Intelligence) to AI (Artificial Intelligence).

To prepare business data for future needs, Amalgam Insights recommends the following steps:

First, improve data collection. This means treating all data in your business as something that will be reused to provide value and cleaning up all existing data through data prep, data quality, and data transformation tasks. It also means putting data into the right format: the age of the relational database as the only tool for analytics is disappearing as non-relational and NoSQL databases have come to the forefront and graph databases like Neo4j and Amazon Neptune finally start their ascendent rise as relationship analytics and semantic search start to eclipse standard Boolean AND, OR, NOT and SQL-based logic.

This isn’t to say that SQL is going anywhere. I still recommend that anybody using data start with a strong foundational knowledge of SQL, as this is probably the only skill I learned 20 years ago that I still use on a regular basis. Skilled relational data querying will always have an important role in the business world. But for business analytics and data managers trying to figure out what is next, consider how to expand your data sources, data quality, and data formats to fit what your company will ask for next.

Second, contextualize your data. One of my favorite sayings, first attributed to Jason Scott, is that “Metadata is a love note to the future.” The ability to prioritize, categorize, and contextualize data sources, fields, and relationships is vital to supporting the future of machine learning and natural language analysis. This means supporting data catalogs, data unification, and master data management tools to bring data together. This stage of data maturity is easy to ignore because it requires getting business context from relevant stakeholders to manage and define data. Given that it can be hard enough to get business users to simply enter data accurately and consistently, the effort to get data definitions and context can be intimidating. But this is a necessary precursor to having “smarter” data and to making the “smarter” decisions that businesses are promised by analytic and machine learning solutions. And the combination of data prep, cleansing, and context make up the majority of work that data scientists end up doing as they try to create relevant models. Solutions that Amalgam Insights recommends most often in this area include Alation, Atlan, Collibra, Informatica, Qlik, Talend, Unifi, and the offerings from megavendors SAP, Oracle, and IBM.

Third, make visualization tools and outputs ubiquitous. Every person in the company should have access to relevant metrics that drive the company. It’s 2020: we’re beyond the time of Skynet and the Terminator, Blade Runner, HAL, and other iconic cinematic visions of the future. The very least we can do is make basic charts and graphs available and accessible to all of our co-workers. Find out what prevents line-level employees from accessing and using data and break down those barriers. Amalgam Insights’ experience is that this challenge comes from a combination of not knowing how to find the right data and how to form the right charts. The answer will likely come from a combination of natural language enhancements driven by the likes of ThoughtSpot, Narrative Science, and Tellius as well as visualization and reporting specialists such as Yellowfin and Toucan Toco and embedded analytics specialists such as Logi Analytics and Izenda.

Fourth, shift from reporting and discovery to predictive analytics. Over the past decade, Tableau has been a fantastic tool for data discovery and continues to lead the market in helping companies to find out what is in their data. However, companies must start thinking of data not only in terms of what it tells us about the present, but how it helps to structure our work and forecast what is next. Data can be used to structure descriptive and predictive models through iterative and guided machine learning. Google’s work with Tensorflow stands out as an end-to-end machine learning solution. During Amalgam Insights’ short existence, DataRobot has quickly risen to become a leader in automated machine learning and its acquisitions of Nexosis for accessibility, ParallelM for MLOps, and Paxata for data prep help have stood out. Microsoft Azure, Amazon Web Services, and IBM Watson also have their own services as well: there are a variety of options for modeling data.

By taking these steps, you can ensure that your data does not fall prey to a premature death as it is rendered obsolete or surrounded by enough technical debt to become functionally useless. If you have any questions on how to better support your data from a future-facing perspective, please contact us at research @ to set up a consultation.

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Career Advice for the Technology Expense Analyst

I was recently chatting with Andi “TEMGirl” Pringle on LinkedIn about career options and skills for the telecom and technology expense analysts. Given that most of my jobs over the past 20 years have been related to telecom billing and expenses, I have a few opinions on this topic. So, to start with…

First, here’s the reality. Telecom expense management is a commoditized job. Telecom spend is not growing, on a global basis, from year to year and CIOs don’t think of telecom as one of their top priorities compared to digital transformation, cybersecurity, process automation, artificial intelligence, or customer experience.

So, where can you go from here? For now, if you’re managing $10 million or more a year in spend, then your efforts should be preventing enough to justify your salary on a revenue per employee basis. Part of your job is to show your manager that your efforts are saving several hundred thousand dollars a year or more by finding those Zero use circuits and phones, optimizing services, and keeping people up and running because nobody will do it for you.

But you also need to upgrade your skills for the long run. Telecom will continue to become just another app running on the network and cloud computing has already eclipsed telecom as being more strategic in importance even though the global market for cloud computing is still only about $250 billion compared to the $1.4 trillion on telecom.

So, there’s a few different directions you can go in depending on whether you want to focus more on the data, finance, technology, project management, strategy, or consulting aspects of the job.

Data Science/Analyst: If you want to dig deeper into the data, you need to understand relational databases and then how to deal with the statistical modeling and analysis of data. Start by learning SQL, the lingua franca of data and the one technical skill that I’ve used consistently over the last 20 years. Then you’ll need to use Python, and/or R along with statistics and calculus classes to understand modeling and to know what you’re doing with your statistical and modeling libraries. The data science role is all about fitting the right algorithms and statistical models to your data, but it all starts with the database and setting up queries. This is actually where I started when I got into telecom, as I had both a computational chemistry and a competitive fantasy baseball background where I’d work on tweaking player forecasts and performance variances. Back then, we used SAS and SPSS rather than R, but tools change over time.

Accounting: Learn some basic financial and managerial accounting as well as micro and macroeconomics. These classes will help you to track costs more effectively, get some business context for costs, and to broaden your skills from telecom-specific cost management to business-wide cost management. The differences aren’t enormous and, frankly, I think telecom expense is one of the hardest costs to manage. A project management or operations management course doesn’t hurt either, as a lot of this role is understanding costs, resources, and business drivers for planning and forecasting. But having an accounting and basic finance background will allow you to translate IT cost management to a broader planning and budgeting capability. This was what Planful CFO Shane Hansen spoke about at our recent Technology Expense Management Expo.

IT Management: Amazon is the new Cisco and there is more new cloud spend this year than telecom spend. It all goes back to tracking storage, network, and compute units across every service, but dig into the service types and learn about cloud services just as you’ve learned about USOCs, FIDs, and service order fields. Cloud providers are the new telcos in terms of being the providers that power IT. Interestingly, a lot of these cloud bills are in the hands of cloud architects and developers who are learning to manage cloud costs from scratch. This management practice is often not called Cloud Cost or Cloud Expense Management (because that would be too easy) but is also called FinOps or a section of Cloud Service Management. We had multiple sessions on cloud infrastructure and software management at the TEM Expo from Corey Quinn, Robert Lee Harris, and Lukas Smith.

Project Management: The PMP is the key certification here. Even if you don’t work on getting the certificate, since some of their materials are starting to get dated, their recommended topics and PMBOK are a helpful starting point. One of the reasons I was glad that Upland Software was an exhibitor at the TEM Expo is that they provide both technology expense and project management software together. I think it’s fundamentally important to have a single toolset to manage projects and cost structures. This is actually a trend in the telecom expense world as a number of solutions start to have SD-WAN or network project management modules as a part of their solution. I think the TEM players will be pushed to go farther.

Managed Service Providers: Being on the vendor side can be an interesting way to work with multiple organizations, sometimes at once, to figure out what similarities and differences exist beween organizations. It can be easy to get stuck in the specificities of your own organization and miss out on some of the best practices and innovations that exist in the market at large because they don’t align with your own organization’s specific governance and compliance issues. Also, being on the vendor side can be a gateway into learning how the management of TEM as a business works and can be a gateway either into moving to service, product, and consulting roles or to become a manager or to learn how to be a full-time consultant on your own.

And finally, if you enjoy either teaching the topic or solving a specific type of TEM problem, you may be better off either as a consultant or industry analyst. (Note: this step requires you to be part of the front office and to either develop or hone your sales chops!) This is the leap I took 12 years ago when I became an industry analyst and I’m always glad to discuss how I did it and where you can learn this craft.

If you’re currently a telecom expense analyst or manager, I highly encourage you to go in one or more of these directions to upskill yourself and continue moving up in your career. If you have any questions about any of these paths, please don’t hesitate to ask me at hyoun @ amalgaminsights. com.