I have a query, my Current Salary is 3.15 Lacs with 3 years experience in Customer service , I applied for new position in Airbnb and salary negotiation is next step, how to know what are the market standards for this job and as per discussion with other employee with same experience , he is getting 5 Lacs in that company but asking for 5.5 lacs is like 70% , I was hired by my last company during pandemic and was offered no raise from my previous salary
Is it recommended to ask for 66% raise?
What data sources will be used, how the data will be delivered from the client, what the ingestion process looks like, QA process, where it’s stored, how it’s delivered, transformation process, maybe assumptions about the data, frequency of various steps, where there’s automation, maybe size of the sets, field enumeration. responsibility matrix
Usually a powerpoint with lots of screenshots.
Probably add the 'intended' downstream consumers of the data and potential alignment to use cases of importance (if the data strategy is aligned with the much vaunted 'analytics vision' oooohhhhh.....im trembling with excitement)
Also. More advanced data strategies consider options to commercialize internally generated data sets...e.g. retailer scanner data, e comm and brick and mortar loyalty program data, industry significant sensor data, etc
Strategy is assessing current state, define future state, conduct fit gap and come up with road map. It means different to different levels in org hierarchy. Key areas to define strategy- data architecture, security, data quality, governance, data integration, master data management , cloud road map, change management.
A .ppt
Lolz. Whenever a client asks what the deliverable will be. I want to say information on a ppt. and / excel. It will be perfect to talk about 1x and then put on your shelf
Why -Start with your business objectives (better reporting, analytics, data quality , info security etc.)
What - list your prioritized data initiatives that will help achieve the business objectives (data aggregation initiative could be one of those).
When - Specify your timeline (data strategies are not for perpetuity - apply for a certain time period based on business objectives)
How - explain approach- tactical, long term, operational etc. For the data aggregation initiative, you could go into the data acquisition strategy etc.
At the minimum, data strategy should cover why”, “what” and “when”... you could include “how”, if applicable to your situation (if you haven’t got buy-in on “what”, “how” may be premature)
Depends on how you define strategy.
I would split between strategy and implementation considerations.
In the case of implementation I would agree with other comments on here. For strategy, I would determine the company’s position towards data (offensive vs defensive). Their position has major implications on how to make decisions for implementation. There is a great article on HBR - What‘s your data strategy. Worth a read. Received great feedback from client after working with their board on strategic data positioning.
Agreed. The implementation part is in the "plan" rather than the strategy. An important but seperate document.
People process tech. Include a vision, roadmap, roles. Job done
Came here to say something , but everyone else covered.
So I leave you with ... a data strategy deliverable looks like every other data strategy deliverable 🤓
Buy the DMBOK and you will have everything you need then look at gartner
Data as a service, data lakes, agile analytics, AI/ML, big data are some buzzwords to throw in. Lot of these deliverable needs to be tweaked to horizontal and vertical integration across company.
I assume that data strategy would revolve around data capture, data storage + warehousing strategy, building technology stack to optimize costs (ie ALL about pipeline, etc.)
That's high level stuff, fit for PPT
C2 it means conceptual logical physical models
Thanks all for posting. I’ll attempt to summarize:
1) defining the approach to using data based on the companies competitive position and current data assets
2) defining the way companies can build data and analytics capabilities
3) defining the current and future state architecture that can support data and analytical decision making
I can’t edit this, but the last bullet is not good.
1. Roles and Responsibilities
2. Project Timeline
3. Methodology
4. Processes
Vision, high level requirements, current state architecture, future state architecture, roadmap
Depends on audience as well.
If it’s going to face Transformation offices and business stakeholders, too - also cover how data will be applied and used for current processes (i.e., now that you have a data warehouse and a AIML center of excellence - what’s the business value on: cost savings, operational improvement, new revenue streams, cross-sell/up-sell).
Helps the client sell the work to their internal stakeholders.
Strategy would consist of three key things, across time (having a time view is a mandate) -
1. Milestones to achieve the larger goal
2. Overview of actions/behaviors you need to exhibit to meet the milestones
3. Resources required
Articulating all of this makes the client realise feasibility and scope. Gives them a starting point and a tangible measure of progress
.ppt . Since it’s a strategy document it wouldn’t hurt to introduce some data related key initiatives and project them forward. Since the „data“ term is broad, I‘d clarify what needs to be included. Data - infrastructure, platforms, applications, analytics, interfaces?
Something that no one can actually use a.k.a pretty slides!
Anyone have any good books or courses they can recommend? Want to learn data architecture quickly with the free time I have while unemployed.
Data architecture is not something you learn quickly.
Check out iasaglobal.com if you want to be a competent IT architect.
Data architecture crosses OLTP, Graph, and OLAP/BI/Big Data technologies. Then there's modeling, data governance, and data quality to learn.
Hence why i say you can't do this quickly, but you can do it.
Don't take too much of a dev mindset into architecture as you need to work on abstracts, communication and other soft skills.
Check C4s recommendation: DMBOK is all you need for a start
Really depends on what you are trying to achieve and your past experience. Personally, I would recommend Azure Solution Architect Cert to everyone, as it involves solid foundation and partly advanced knowledge of everything, that comes into play before application layer. But thats just my humble opinion.
In practice, I dislike most theoretical approaches, because tbh, I took part in exactly one green field pilot in the past so far. Many assumptions don‘t hold up to that, so knowing them doesn‘t hurt, but you have to navigate your way around that.