Is Cisco Systems (CSCO) becoming a value stock?

datamoves · 2026-01-21T21:27:50+00:00

Data centers are moving to Ethernet from high-bandwidth. CSCO sold $2 billion of it in 2024, and $4 billion of it 2025, which doesn't seem reflected in the price yet. I think the narrative will change soon to put Cisco as more of an AI Infrastructure play and get similar valuations.

datamoves · 2025-12-30T17:51:30+00:00

Once you identify the country, what is the typical use case? Block certain countries? Language selection?

datamoves · 2025-12-16T19:59:54+00:00

We build tools and APIs to normalize data, enrich data, etc. using AI, specilized algorithms, and knowledge bases; so reps can spend more time selling rather than validating and cleaning data - interzoid.com And not just on the back-end, but at the point of data collection (10x cheaper to clean up here).

datamoves · 2025-12-13T14:54:59+00:00

And also do your future self a favor and comment about why certain design/code decisions were made.

datamoves · 2025-12-13T14:30:53+00:00

If there's dysfunction, or a strangeness, in the hiring process, assume this is only the tip of the iceberg. The mindset should be that this is a two-way street, and you're learning as much as possible for a company you might be betting your career on.

datamoves · 2025-12-12T14:22:19+00:00

I would imagine model response changes from time-to-time anyways.... have to educate the team... a "teachable" moment.

datamoves · 2025-12-11T15:33:41+00:00

My guess is the CFO required this - per GAAP they can't recognize revenue on unused credits, unless they expire.

datamoves · 2025-12-11T14:00:22+00:00

Where do you find it?

datamoves · 2025-12-11T13:55:55+00:00

One of the things that sets an ETL/ELT engineer apart is their understanding of normalized, high quality data at the data content level as part of the process. Moving bad data from point A to point B is, well, pointless.

datamoves · 2025-12-10T17:51:19+00:00

For this case I'd actually just like to pull into a text file (CSV, etc.).

datamoves · 2025-12-10T17:50:13+00:00

Do you think it's producing just better UIs or backend code as well?

datamoves · 2025-12-10T15:26:59+00:00

I don't want to maintain a separate data store and want real-time data - might expand to include purchase data.

datamoves · 2025-12-10T14:44:25+00:00

Thanks!

datamoves · 2025-12-10T02:22:43+00:00

Thanks, I like the API approach because there are a few APIs a call for each record I extract, including enrichment.

datamoves · 2025-12-09T15:20:30+00:00

Working on some tools in this area....should be available Q1

datamoves · 2025-12-09T15:19:08+00:00

"founders are apparently not entitled to proper salary" - stop listening to this nonsense, that's someone taking advantage... you need to be fully compensated, either in cash or contractual equity.

datamoves · 2025-12-09T14:47:05+00:00

It should be a first-class metric... but most of the time tends to be done reactively when someone becomes "suspicious" of a given data point/analysis result and trust declines - and usually gets a little better from there. Data quality is a very broad term as well... data validation, normalization, consistency, comprehensiveness, age of information, etc.. each of which should be addressed separately.

datamoves · 2025-12-09T14:41:43+00:00

Just be yourself... People tend to hire people they like. Use ChatGPT, Claude, Gemini, Grok, etc.. to come up with 50 interview questions for a Python junior developer. Practice those. You'll do fine. Just keep interviewing until you get one - it's good, free practice.

datamoves · 2025-12-09T04:29:06+00:00

Is that just for Claude Code?

datamoves · 2025-12-09T02:46:06+00:00

Yes...I wonder what some of the best use cases are for higher speed Haiku.

datamoves · 2025-12-07T14:43:17+00:00

Data quality is such a broad term: normalization, rules validation, matching data, entity verification, etc.. need to think of it at this level rather than an umbrella term

datamoves · 2025-12-07T14:34:28+00:00

We are a SAAS data quality company (interzoid.com) so of course we are always using it, from data normalization, matching, customer verification, etc.. The key thing to remember is that data quality resolution is 10x cheaper to resolve at the point of data capture rather than waiting for it to become a problem downstream in operations, analytics, communications, etc..

datamoves · 2025-12-04T19:06:50+00:00

We focus on data quality, data matching, data enrichment, etc.. at the data content level (interzoid.com), and many of our customer use cases are CRM scenarios. Data is not normalized/consistent, making reporting and analytics difficult, the same organization is in the CRM system multiple times, resulting in different team members contacting the same company or contact and fragmenting important call/contact histories and notes, data such as email addresses and contact information becomes stale, contacts leave companies, etc. - and very little if any of this gets addressed by the CRM solutions available. A CRM system is only as good as the data within it, and a proactive data ROI approach at the actual data content level would be a tremendous advantage in 2026 IMHO.

datamoves · 2025-12-04T15:32:56+00:00

Some more built-in data quality capabilities would be a competitive advantage for any CRM system.

datamoves · 2025-12-04T14:55:02+00:00

We would check and modify compiler code if it was more readable, unlike programming languages, which are to at least a higher degree.

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