Jiro Ono, Takashi Saito, Eki Ichimura, Isao Amano—these men are legendary sushi chefs. It’s a dream of mine to sit down at one of the eight seats of Saito-san’s Sushi Saito in the Roppongi district of Tokyo. I would happily drop a few hundred dollars on a single dinner.

The reason why people will pay so much for a meal is simple: expertise. A master chef has deep knowledge of which fish will make the best sushi during any season. They have relationships with the fishermen, distributors and wholesalers that will treat the fish with respect. Once they get the fish, they know whether it’s best served immediately, or aged as you might do with beef. And they know how to serve it come day-of preparations—whether it should be served raw or seared, with topping or without.

Talk to any connoisseur and they’ll say that the true expertise of a sushi chef lies in their preparation of rice. For all the things mentioned above, the same is true here—know what rice is best, how to cook it, season it, and serve it so that it makes the fish shine. Temperature and texture of the rice is key, in addition to the taste itself.

Finally, there’s the operations of the restaurant and its customers. A brilliant sushi chef can serve multiple customers at once. They know where each customer is in their progression through the meal. They make sure to keep the rice at the proper temperature and (sometimes) they carry on conversation with guests. And on top of that, they manage and train staff, and apprentices will often go on and take what they learn to create their own restaurants with their own unique spins on cuisine.

Now, I know you’re not here for a sushi lesson. I mention this because it reminded me of Max’s very deep-dive into the world of alternative data, which can be found here.

Data is king, but when it comes to alt data, users are finding that cost isn’t necessarily the greatest barrier to incorporating these datasets, but the challenge of integrating them. If you want a real advantage, you need expertise in handling data—as sources repeatedly told Max, to stand out as a data provider, you have to (a) own the data, and (b) do something unique with it. As an end-user firm, you need to use data quickly and get the most out of it to stand out.

To go back to the analogy above, think about the term sushi—there are many different ways to prepare raw fish. For me, when I say sushi, I’m really talking about sashimi, which is just the fish itself, with a bit of soy sauce and wasabi. There are sushi rolls. There’s proper sushi, which is raw fish combined with rice. And under each of those disciplines, there are seemingly endless mixtures that can be created.

A sushi master can command high prices for their food due to their years of experience in manipulating ingredients and honing their craft. As some of the biggest financial institutions are learning, the same is true when it comes to the handling and manipulating of alternative data alongside traditional in-house datasets.  

In his article, Max makes note that BlackRock recently acquired Ark Data, a start-up that helps alt data providers to package their data to potential clients, and helps clients to assess and ingest alt datasets. The start-up was created by Rich Newman and Tim Gavin, and includes Bryan Lenker, all of whom are long-time FactSet alums. Combined, the trio has about 100 years’ worth of data management experience.

From the story: Sources say Ark was in the process of fundraising, and that BlackRock—which is building out its own cloud-based data and analytics offering, Aladdin Studio and Aladdin Data Cloud, in partnership with Snowflake—saw in Ark “an aligning of interests,” and made an offer to acquire the key people behind Ark but not any specific technology assets. … One source familiar with the situation says, “The way to look at the transaction is not to think of it as an acquisition where BlackRock acquired Ark’s business and technology, but as an acquisition of know-how and intellectual property.”

Think about how huge BlackRock is; people may forget, but during the 2008 crisis, it acquired Barclays Global Investors, which alone handled so much order flow that if it were an exchange it would have been something like the third-largest in the world. So, today, BlackRock processes enormous amounts of data—order data, supporting data, fundamental data, contextual data, etcetera, etcetera. As a result, it has big opportunities to do things with that data. Add Aladdin with its connectivity to the buy side, and all of the sudden they’re also potentially one of the biggest infrastructure providers and data vendors in the world. So for BlackRock, the Ark Data deal makes complete sense as it tries to unify its own internal data to better blend with outside datasets.

The question then becomes, who will look to follow in the footsteps of BlackRock? State Street has been on something of an acquisition spree, having most recently bought Brown Brothers Harriman Investor Services. With the blending of the Alpha and Charles River platforms, along with its asset and wealth management businesses, it’s in a similar position as BlackRock. Goldman Sachs has prided itself on hiring the best and brightest, and then building in-house…but in this changing landscape, it might look for outside help.

And then there’s the likes of Google and Microsoft. As we’ve written before, there are some who believe that Big Tech will look to make a splash in the market data space via a major acquisition, but these companies could also prove more valuable if they acquire a data “wrangler and untangler” to match their deep data analytics expertise.

Expect to see other acquisitions (Crux Informatics? Althub? Alqami?) similar to the BlackRock-Ark Data deal for similar reasons. People are willing to spend exorbitantly to get raw fish prepared by individuals with decades of experience…that’s true of companies who can prepare data in new and unique ways that deliver unforgettable alpha, instead of an unforgettable meal.

Think I’m wrong? Wanna talk sushi? Hit me up: anthony.malakian@infopro-digital.com