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Data: Lost in Translation

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Whether you are setting up an ongoing integration or preparing for a one-time migration, there will be situations where a ‘single-select’ or a similar field type’s data in one system is not what the other system accepts. The list values may be very similar but not the same in both systems. Contextually as a user you know what values equate to each other, but if they aren’t identical then how do you consistently automate this in your integration or migration?

To do this, we use a method often referred to as a data translation, a lookup, or a cross reference table. Regardless of what it’s called, this method of translating values always follows the same basic structure and principle.

The Structure

To start, you will need a table of data containing at least two columns. Each column represents one of your systems and contains all the selectable options for the ‘connected’ fields from each system. Each row in the table is where you connect the related list value options between the columns. Connecting the related values in the rows is the most important part of the table since this is how you define which values translate to each other.

The Principle

Once you have your table assembled, you are ready to put it to use translating that field’s data between each system. This part often makes more sense with a visual explanation, so let’s start with a basic example scenario.

  • In this scenario we have two systems which we are integrating with each other. We’ll call them ‘System A’ and ‘System B’.
  • Within this integration we are mapping list fields (i.e. drop-down select or single-select) to each other between the two systems. We’ll call them ‘Field A’ and ‘Field B’ respectively.

In the illustration below, we have built our table that connects our list values for the field in each system:

Picture1

Now let’s say our integration were to sync 4 records from ‘System A’ to ‘System B’, and the below list represents the value from ‘Field A’ on each of these 4 records:

Picture2

Our integration would then take the Field A value in each record from System A and find a match in the Field A column of our table we built before. Once that match in the Field A column is found we then take the Field B value from the same row and use that for the new field value that we will sync to the 4 corresponding records in System B. The illustration below illustrates this by showing you the original values from System A on the left and then the new translated values going to System B on the right.

Picture3

The Takeaway

Knowing how to translate your data between systems is exactly like what translators do to communicate a message from one language into another. So, mastering the structure and principle behind translating your data is how you or your integration becomes the translator and ensures that your data never gets lost in translation.

Need help getting data from one system into another?

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Source: http://blog.trujay.com/data-lost-in-translation

Blockchain

SingularityNET Partners With Ocean Protocol Prior to the AI-Based DeFi Fund Launch

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[Press Release – Amsterdam, Netherlands, 18th May 2021]

SingularityNET’s first DeFi spin-off project, SingularityDAO, is announcing today their partnership with leading decentralized data provider Ocean Protocol.

The collaboration will see the OCEAN token’s inclusion in SingularityDAO’s index fund/investment portfolio. Moreover, SingularityDAO is designed to leverage AI at multiple levels: AI manages dynamic token-sets, executes predictive market-making strategies to provide liquidity for these token-sets on DEXs, and predictively models hedging strategies.

All this AI requires a lot of data to learn and improve, which is why SingularityDAO is a natural user of Ocean data sets – data sets published via Ocean Market (and other Ocean-based markets) into the Ocean ecosystem. The Ocean ecosystem is host to many diverse and varied trading and DeFi data sets. These make excellent candidates for consumption by SingularityDAO’s AI agents to enhance its financial modeling.

I’m really excited by the opportunity to work together with Ocean Protocol, one of the most respectable projects in crypto that has been constantly delivering community-driven, decentralized data solutions. SingularityDAO will constantly make use of data to train our ML and I can’t think of a better partner than Ocean Protocol. – Marcello Mari, CEO at SingularityDAO

The news follows the successful completion of a total of $5.2 million raised in three different rounds for the highly anticipated Governance Generation Event on MANTRADAO, which reached its hard cap within less than 2½ hours.

The protocol, described as ‘DeFi meets decentralized AI,’ held the event exclusively for SingularityNET $AGI holders and attracted 5,800 registrations in one week. The token sale raised $1.6 million (8,000,000 SDAO).
The successful Governance Generation Event follows a recent private sale wherein SingularityDAO raised $2.7 million of funding from a number of top-tier investors such as AlphaBit, Marshland Capita, GBV, and SMO Capital. SingulariyDAO’s governance token has been generated on May 13th and distributed on the same day. It is currently trading on Uniswap.

About SingularityDAO

SingularityDAO is a decentralized platform, governed by the SDAO token, tasked with governing DynaSets. DynaSets are diversified baskets of cryptocurrency assets dynamically managed by AI and curated by the protocol. SingularityDAO brings the financial sophistication of AI-managed funds to DeFi, deploying SingularityNET’s AI technology to navigate complex markets.

About Ocean Protocol

Ocean Protocol’s mission is to kickstart a Web3 Data Economy that reaches the world, giving power back to data owners and enabling people to capture value from data to better our world.
Data is a new asset class; Ocean Protocol unlocks its value. Data owners and consumers use the Ocean Market app to publish, discover, and consume data assets in a secure, privacy-preserving fashion.

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Source: https://cryptopotato.com/singularitynet-partners-with-ocean-protocol-prior-to-the-ai-based-defi-fund-launch/

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Blockchain

Bought the Dip? MicroStrategy Purchased $10M in Bitcoin at $43.6K

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Michael Saylor’s NASDAQ-listed company continues with its initiative to purchase sizeable amounts of bitcoins at frequent intervals. The firm said earlier today it had allocated another $10 million in cash in BTC, and its total stash is over 92,000 coins.

  • The founder and CEO of the business intelligence giant announced the latest purchase on Twitter earlier on May 12th.
  • It reads that the firm has bought 229 bitcoins for $10 million in cash at an average price of $43,663 per coin.
  • Keeping in mind the multiple purchases made since August 2020, the firm holds 92,079 bitcoins. MicroStrategy has paid $2.251 billion for its stash, with an average price of $24,450 per token.
  • Although this is far from being the largest single acquisition, as the company once bought more than $1 billion worth of BTC, this one actually comes in a compelling moment.
  • In fact, buying 10 million coins at an average price of $43,663 means that MicroStrategy has taken advantage of a popular narrative in the crypto community – buy the dip.
  • The price of the primary cryptocurrency has suffered severely in the past week or so after Elon Musk announced that Tesla has stopped receiving BTC payments for its electric vehicles.
  • In a matter of days, bitcoin fell from over $58,000 to a three-month low of $42,000.
  • Although losing $16,000 of value in less than a week could be considered a major blow, and some investors disposed of their coins even at a loss, MicroStrategy has reaffirmed its promise to continue buying bitcoin as part of its reserve treasury strategy.
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Source: https://cryptopotato.com/bought-the-dip-microstrategy-purchased-10m-in-bitcoin-at-43-6k/

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Blockchain

JPMorgan’s Securities Services to Offer TradingHub’s Analytics Solutions

The Bank is planning to offer trading analytics solutions to its buy-side clients.

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TradingHub, a trade analytics services provider to the global financial markets industry, today announced that JPMorgan, one of the leading investment banks worldwide, will offer TradingHub’s trading analytics solutions to its institutional clients.

According to the official announcement, JPMorgan’s new offering will include TradingHub’s Transaction Efficiency and Accuracy Monitor (TEAM) solution. TradingHub is currently providing trade analytics services to several investment banks and investment management firms worldwide.

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TEAM is a new tool by TradingHub that enables financial services companies around the world to evaluate execution costs at the order, trade, instrument, or asset class-level, and compare against peers on an anonymized basis.

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Commenting on the latest announcement, Neil Walker, Chief Executive and Founder of TradingHub, said: “We are delighted JPMorgan has identified TEAM as a highly novel and valuable product and is giving its clients access to our market-leading trade execution analytics service. This important relationship with JPMorgan will give more asset managers access to our services in a seamless and efficient manner via its open platform.”

JPMorgan has accelerated its global partnerships since the start of 2021. The US-based financial services provider recently partnered with Singapore’s DBS Bank and Temasek to develop a new blockchain-based platform for cross-border payments.

Transparency

TradingHub mentioned in the latest announcement that the main focus of TEAM is to facilitate buy-side firms in the identification of financial brokers providing the best execution. TEAM also provides greater transparency to sell-side institutions. “Providing clients with access to unique services which help them manage transparency across the trade lifecycle is more important than ever. We’re excited to be working with TradingHub and offer TEAM as part of our growing platform,” Richard Crozier, Head of Product for Data and Analytics at JPMorgan Securities Services mentioned in the official announcement.

JPMorgan is planning to facilitate buy-side clients by providing integrated solutions through an open platform. In the last quarter, JPMorgan posted strong growth in revenues and profit.

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Source: https://www.financemagnates.com/institutional-forex/jpmorgans-securities-services-to-offer-tradinghubs-analytics-solutions/

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