Up until now, paid services like Netflix, Amazon Prime, and HBO have dominated US online video viewing, particularly for long-form, TV-style content. Uptake of ad-supported, TV-style online video has been slower; traditional TV providers control much of this content, and they’ve been cautious about making their programming available outside the lucrative TV bundle. Even if many viewers want to cut the cord, they may not follow through as they realize they cannot get all the content they want. YouTube, of course, has a massive ad-supported online video business that has been growing healthily according to our calculations. However, even YouTube falls short of Netflix in terms of downstream bandwidth consumption, and its estimated ad revenue is only a small fraction of traditional TV ad revenue. For online video ad spend to show meaningful growth, consumer-generated or web-only content won’t be enough. A truly robust online video ad market will require the migration of traditional TV content to digital platforms.
This migration appears to be gathering momentum. Recently, we have seen a number of developments that could drive the uptake of ad-supported online video and that indicate that 2017 could be the year when ad-supported online video starts to make a splash.
Most enterprises aren't fully exploiting real-time streaming data that flows from IoT devices and mobile, web, and enterprise apps. Streaming analytics is essential for real-time insights and bringing real-time context to apps. Don't dismiss streaming analytics as a form of "traditional analytics" use for postmortem analysis. Far from it — streaming analytics analyzes data right now, when it can be analyzed and put to good use to make applications of all kinds (including IoT) contextual and smarter. Forrester defines streaming analytics as:
Software that can filter, aggregate, enrich, and analyze a high throughput of data from multiple, disparate live data sources and in any data format to identify simple and complex patterns to provide applications with context to detect opportune situations, automate immediate actions, and dynamically adapt.
Forrester Wave™: Big Data Streaming Analytics, Q1 2016
To help enterprises understand what commercial and open source options are available, Rowan Curran and I evaluated 15 streaming analytics vendors using Forrester's Wave methodology. Forrester clients can read the full report to understand the market category and see the detailed criteria, scores, and ranking of the vendors. Here is a summary of the 15 vendors solutions we evaluated listed in alphabetical order:
A week ago, my family crowded around our living-room TV to watch the Macy’s Thanksgiving Day parade, and I couldn’t help thinking about the ironic clash between tradition and innovation: On the one hand, we mirrored that classic tableau of the family gathered around a single source of entertainment; on the other, our smart TV offered a distinctly modern viewing experience.
This fine balance between tradition and innovation is widespread — especially in regards to the evolution of TV media. Our Consumer Technographics® data shows that US consumers’ love for TV is unwavering, but the ways in which viewers access content are rapidly changing. Streaming services like Netflix and Amazon Prime have been catalysts for this change; now Comcast’s recently launched Stream TV opens a new avenue for TV consumption that lives somewhere between cable and Internet properties. With Stream TV, Comcast is targeting a growing group of TV lovers who don’t actually have a TV:
Intel has made no secret of its development of the Xeon D, an SOC product designed to take Xeon processing close to power levels and product niches currently occupied by its lower-power and lower performance Atom line, and where emerging competition from ARM is more viable.
The new Xeon D-1500 is clear evidence that Intel “gets it” as far as platforms for hyperscale computing and other throughput per Watt and density-sensitive workloads, both in the enterprise and in the cloud are concerned. The D1500 breaks new ground in several areas:
It is the first Xeon SOC, combining 4 or 8 Xeon cores with embedded I/O including SATA, PCIe and multiple 10 nd 1 Gb Ethernet ports.
It is the first of Intel’s 14 nm server chips expected to be introduced this year. This expected process shrink will also deliver a further performance and performance per Watt across the entire line of entry through mid-range server parts this year.
Why is this significant?
With the D-1500, Intel effectively draws a very deep line in the sand for emerging ARM technology as well as for AMD. The D1500, with 20W – 45W power, delivers the lower end of Xeon performance at power and density levels previously associated with Atom, and close enough to what is expected from the newer generation of higher performance ARM chips to once again call into question the viability of ARM on a pure performance and efficiency basis. While ARM implementations with embedded accelerators such as DSPs may still be attractive in selected workloads, the availability of a mainstream x86 option at these power levels may blunt the pace of ARM design wins both for general-purpose servers as well as embedded designs, notably for storage systems.
But Avoid Ending Up With A Zoo Of Individual Big Data Solutions
We are beyond the point of struggling over the definition of big data. That doesn’t mean that we've resolved all of the confusion that surrounds the term, but companies today are instead struggling with the question of how to actually get started with big data.
28% of all companies are planning a big data project in 2014.
According to Forrester's Business Technographics™ Global Data And Analytics Survey, 2014, 28% of the more than 1600 responding companies globally are planning a Big Data project this year. More details and how this splits between IT and Business driven projects can be found in our new Forrester Report ‘Reset On Big Data’.
Or join our Forrester Forum For Technology Leaders in London, June 12&13, 2014 to hear and discuss with us directly what Big Data projects your peers are planning, what challenges they are facing and what goals they target to achieve.
Since the introduction of the DVR more than a decade ago, consumers have learned they don't have to conform their lives to broadcast programmers' schedules in order to watch their favorite TV shows.
Along come online sources like HuluPlus, or the network's own websites promise even more convenience: Get any episode of any show with no need to remember to record it. But adoption is hampered by the awkward viewing experience of the cramped screens of laptops, tablets, and smartphones.
Welcome to TV viewing in the Age of the Customer. Consumers want their favorite shows when they want them, on their preferred device, with little or no effort on their part.
Linear TV, DVRs and today's online viewing experience all fail on at least one of these dimensions. Viewers increasingly cobble together a mix of sources and devices to create this level of convenience, and each of these players vies to capture more of viewers' time by improving its offering.
In my new report, "How Online Video Will Challenge DVRs' Role," I delve into how these two sources of video entertainment vie to meet consumers' increasing expectations. DVRs have the advantage of incumbency, while online viewing offers greater flexibility.