Friday, August 1, 2014

Welcome Document.md

Welcome to StackEdit!

Hello, I am your first Markdown document within StackEdit1. Don’t delete me, I can be helpful. I can be recovered anyway in the Utils tab of the Settings dialog.


Documents

StackEdit stores your documents in your browser, which means all your documents are automatically saved locally and are accessible offline!

Note:

  • StackEdit is accessible offline after the application has been loaded for the first time.
  • Your local documents are not shared between different browsers or computers.
  • Clearing your browser’s data may delete all your local documents! Make sure your documents are backed up using Google Drive or Dropbox synchronization (see Synchronization section).

Create a document

The document panel is accessible using button in the navigation bar. You can create a new document by clicking the New document sub-menu in the document panel.

Switch to another document

All your local documents are listed in the document panel. You can switch from one to another by clicking a document in the document panel or you can also use Ctrl+[ and Ctrl+] to toggle documents by most recently used.

Rename a document

You can rename the current document by clicking the document title in the navigation bar.

Delete a document

You can delete the current document by clicking the Delete document sub-menu in the document panel.

Export a document

You can save the current document to a file using the Export to disk sub-menu from the menu panel.

Tip: See Publish a document section for a description of the different output formats.


Synchronization

StackEdit can be combined with Google Drive and Dropbox to have your documents centralized in the Cloud. The synchronization mechanism will take care of uploading your modifications or downloading the latest version of your documents.

Note:

  • Full access to Google Drive or Dropbox is required to be able to import any document in StackEdit. Permission restrictions can be configured in the settings.
  • Imported documents are downloaded in your browser and are not transmitted to a server.
  • If you experience problems saving your documents on Google Drive, check and optionally disable browser extensions, such as Disconnect.

Open a document

You can open a document from Google Drive or the Dropbox by opening the Synchronize sub-menu and by clicking Open from.... Once opened, any modification in your document will be automatically synchronized with the Google Drive / Dropbox file.

Save a document

You can save any document by opening the Synchronize sub-menu and by clicking Save on.... Even if your document is already synchronized with Google Drive or Dropbox, you can export it to a another location. StackEdit can synchronize one document with multiple locations.

Synchronize a document

Once your document is linked to a Google Drive or a Dropbox file, StackEdit will periodically (every 3 minutes) synchronize it by downloading/uploading any modification. Any conflict will be detected, and a local copy of your document will be created as a backup if necessary.

If you just have modified your document and you want to force the synchronization, click the button in the navigation bar.

Note: The button is disabled when you have no document to synchronize.

Manage document synchronization

Since one document can be synchronized with multiple locations, you can list and manage synchronized locations by clicking Manage synchronization in the Synchronize sub-menu. This will let you remove synchronization locations that are associated to your document.

Note: If you delete the file from Google Drive or from Dropbox, the document will no longer be synchronized with that location.


Publication

Once you are happy with your document, you can publish it on different websites directly from StackEdit. As for now, StackEdit can publish on Blogger, Dropbox, Gist, GitHub, Google Drive, Tumblr, WordPress and on any SSH server.

Publish a document

You can publish your document by opening the Publish sub-menu and by choosing a website. In the dialog box, you can choose the publication format:

  • Markdown, to publish the Markdown text on a website that can interpret it (GitHub for example),
  • HTML, to publish the document converted into HTML (on a blog for example),
  • Template, to have a full control of the output.

Note: The default template is a simple webpage wrapping your document in HTML format. You can customize it in the Advanced tab of the Settings dialog.

Update a publication

After publishing, StackEdit will keep your document linked to that publication which makes it easy for you to update it. Once you have modified your document and you want to update your publication, click on the button in the navigation bar.

Note: The button is disabled when your document has not been published yet.

Manage document publication

Since one document can be published on multiple locations, you can list and manage publish locations by clicking Manage publication in the menu. This will let you remove publication locations that are associated to your document.

Note: In some cases, if the file has been removed from the website or the blog, the document will no longer be published on that location.


Markdown Extra

StackEdit supports Markdown Extra, which extends Markdown syntax with some nice features.

Tip: You can disable any Markdown Extra feature in the Extensions tab of the Settings dialog.

Note: You can find more information about Markdown syntax here and Markdown Extra extension here.

Tables

Markdown Extra has a special syntax for tables:

Item Value
Computer 1600Phone|12
Pipe $1

You can specify column alignment with one or two colons:

Item Value Qty
Computer 1600|5||Phone|12 12
Pipe $1 234

Definition Lists

Markdown Extra has a special syntax for definition lists too:

Term 1
Term 2
Definition A
Definition B
Term 3

Definition C

Definition D

part of definition D

Fenced code blocks

GitHub’s fenced code blocks2 are also supported with Prettify syntax highlighting:

// Foo
var bar = 0;

Tip: To use Highlight.js instead of Prettify, just configure the Markdown Extra extension in the Settings dialog.

Note: You can find more information:

  • about Prettify syntax highlighting here,
  • about Highlight.js syntax highlighting here.

Footnotes

You can create footnotes like this3.

SmartyPants

SmartyPants converts ASCII punctuation characters into “smart” typographic punctuation HTML entities. For example:

ASCII HTML
Single backticks 'Isn't this fun?' ‘Isn’t this fun?’
Quotes "Isn't this fun?" “Isn’t this fun?”
Dashes -- is en-dash, --- is em-dash – is en-dash, — is em-dash

Table of contents

You can insert a table of contents using the marker [TOC]:

MathJax

You can render LaTeX mathematical expressions using MathJax, as on math.stackexchange.com:

The Gamma function satisfying Γ(n)=(n1)!nN is via the Euler integral

Γ(z)=0tz1etdt.

Tip: Make sure you include MathJax into your publications to render mathematical expression properly. Your page/template should include something like this:

<script type="text/javascript" src="https://stackedit.io/libs/MathJax/MathJax.js?config=TeX-AMS_HTML"></script>

Note: You can find more information about LaTeX mathematical expressions here.

UML diagrams

You can also render sequence diagrams like this:

Alice->Bob: Hello Bob, how are you?
Note right of Bob: Bob thinks
Bob-->Alice: I am good thanks!

And flow charts like this:

st=>start: Start
e=>end
op=>operation: My Operation
cond=>condition: Yes or No?

st->op->cond
cond(yes)->e
cond(no)->op

Note: You can find more information:

  • about Sequence diagrams syntax here,
  • about Flow charts syntax here.

  1. StackEdit is a full-featured, open-source Markdown editor based on PageDown, the Markdown library used by Stack Overflow and the other Stack Exchange sites.
  2. GitHub Flavored Markdown (GFM) is supported by StackEdit.
  3. Here is the text of the footnote.

Wednesday, August 28, 2013

Positions and titles related to Data Analytics


  • Advanced Analytics Analyst
  • Analyst, Trade Strategy
  • Analytics Consultant
  • Analytics Lead
  • Assistant VP, Senior Marketing Analyst
  • Assistant VP, Senior Risk Analyst
  • Associate Marketing Analyst
  • Associate Software Developer
  • Associate Solution Architect
  • Business Analyst
  • Business Analyst Associate
  • Business Intelligence Analyst
  • Business Planning Analyst
  • Category Analyst
  • Consultant
  • Consultant – Portfolio Analytics
  • Corporate Data Analyst
  • Data Analyst
  • Data Miner
  • Data Scientist
  • Executive Associate
  • Financial Analyst
  • Human Capital Associate
  • Informatics Senior Specialist
  • Lead Analytics Consultant
  • Management Consultant
  • Manager, Analytics
  • Manager, Pricing and Promotion Analytics
  • Manager, Reporting and Analysis
  • Managing Consultant
  • Marketing Analyst
  • Marketing Database Analyst
  • Pricing Analyst
  • Pricing Representative
  • Procurement Analyst
  • Procurement Specialist
  • Research Analyst
  • Risk Analyst
  • Risk Manager
  • Sr. Analyst
  • Sr. Analyst – Strategic Planning
  • Sr. Associate
  • Sr. Associate Analytical Consultant
  • Sr. Associate Software Developer
  • Sr. Associate Systems Engineer
  • Sr. Category Analyst
  • Sr. Clinical Informatics Analyst
  • Sr. Consultant
  • Sr. Data Analyst
  • Sr. Data Miner
  • Sr. Data Scientist
  • Sr. Informatics Specialist
  • Sr. Manager, Marketing
  • Sr. Manager, Customer Knowledge & Analytics
  • Sr. Operational Analyst
  • Sr. Optimization Analyst
  • Sr. Research Analyst
  • Sr. Risk Analyst
  • Sr. Statistical Analyst
  • Sr. Statistical Modeler
  • Sr. Statistician, Operational Research
  • Sr. Web Analyst
  • Statistical Modeler
  • Systems Engineer – Financial Analytics
  • Technical Program Manager
  • VP, Geospatial Analytics Manager
  • VP, Marketing Analytics
  • VP, Retail Site Selection Manager

Friday, August 16, 2013

Data Analytics – Open Source Landscape

Data Analytics Open Source Landscape

 

For the latest version, please visit http://www.bigdata-startups.com/open-source-tools/

Data Analytics : different areas

  • Agile BI
  • Big Data Analytics
  • Business Analytics
  • Business Intelligence
  • Data Analysis and Design
  • Data Management
  • Data Warehousing
  • Performance Management
  • Program Management
  • Master Data Management

Agile BI

Agile business intelligence addresses a broad need to enable flexibility by accelerating the time it takes to deliver value with BI projects. It can include technology deployment options such as self-service BI, cloud-based BI, and data discovery dashboards that allow users to begin working with data more rapidly and adjust to changing needs.

To transform traditional BI project development to fit dynamic user requirements, many organizations implement formal methodologies that utilize agile software development techniques and tools to accelerate development, testing, and deployment. Ongoing scoping, rapid iterations that deliver working components, evolving requirements, scrum sessions, frequent and thorough testing, and business/development communication are important facets of a formal agile approach.

Big Data Analytics

Big data analytics is the application of advanced analytic techniques to very large, diverse data sets that often include varied data types and streaming data.

Big data analytics explores the granular details of business operations and customer interactions that seldom find their way into a data warehouse or standard report, including unstructured data coming from sensors, devices, third parties, Web applications, and social media - much of it sourced in real time on a large scale. Using advanced analytics techniques such as predictive analytics, data mining, statistics, and natural language processing, businesses can study big data to understand the current state of the business and track evolving aspects such as customer behavior. New methods of working with big data, such as Hadoop and MapReduce, also offer alternatives to traditional data warehousing.

Business Analytics

Business analytics allows users to examine and manipulate data to drive positive business actions. Armed with advanced analytics insights, business users can make well-informed, fact-based decisions to support their organizations’ tactical and strategic goals.

Business analytics includes advanced techniques such as spatial analytics, customer analytics, and enterprise decision management. Analytic applications bundle tools for data access, dashboard reporting, scorecards, and analytics into packages. Predictive analytics identify relationships and patterns in large volumes of data to create predictive models. Text mining parses unstructured data and merges it with structured data to support user queries, reports, and analyses. “Big data” analytics implement MapReduce, Hadoop, and specialized, non-SQL programming methods to speed insight from huge volumes of data drawn typically from online sources.

Business Intelligence

Business intelligence (BI) unites data, technology, analytics, and human knowledge to optimize business decisions and ultimately drive an enterprise’s success. BI programs usually combine an enterprise data warehouse and a BI platform or tool set to transform data into usable, actionable business information.

Agile BI utilizes agile software techniques and tools to accelerate development and deployment. (See Agile BI.) In-memory BI exploits the reduced cost and increasing power of computer memory and processing.  Self-service BI enables users to access and analyze data with less dependence on IT resources.  Real-time BI focuses on delivering information to users or systems as events are occurring.  Search integrates access to unstructured content and structured data in reports or dashboards.  Open source and software-as-a-service BI provide alternative licensing and service options.

Data Analysis and Design

Data analysis and design provides the foundation for delivering BI applications. Analysis concentrates on understanding business needs for data and information. Design translates business information needs into data structures that are adaptable, extensible, and sustainable. Core skills include needs analysis, metrics definition, and data modeling.
This BI discipline includes gathering accurate business requirements; designing business rules; analyzing and modeling data; dimensional modeling; key performance indicators (KPIs) and metrics; and testing and documentation.

Data Management

Data management (aka enterprise information management) encompasses techniques for data quality, integration, and governance. It includes all the practices necessary to manage data as a critical enterprise asset.

Data quality includes techniques for name-and-address cleansing, data standardization, verification, profiling, monitoring, matching, householding, and enrichment. Data integration (DI) acquires data from sources and transforms and cleanses it. ETL (extract, transform, and load) is the most common form; others include ELT, customer data integration (CDI), data federation, database replication, and data synchronization. Data integration may be analytic or operational. Data governance boards or com­mittees create and enforce policies and procedures for data usage and manage­ment. (See Master Data Management.)

Data Warehousing

Data warehousing incorporates data stores and conceptual, logical, and physical models to support business goals and end-user information needs. A data warehouse (DW) is the foundation for a successful BI program.
Creating a DW requires mapping data between sources and targets, then capturing the details of the transformation in a metadata repository. The data warehouse provides a single, comprehensive source of current and historical information.
Data warehousing techniques and tools include DW appliances, platforms, architectures, data stores, and spreadmarts; database architectures, structures, scalability, security, and services; and DW as a service.

Performance Management

Performance management (PM) is a powerful tool of organizational change. Companies that define objectives, establish goals, measure progress, reward achievement, and display the results for all to see can turbo-charge productivity and move an organization in a new direction.
Performance management typically involves performance dashboards, scorecards, and other visualization solutions; key performance indicators (KPIs) and metrics; and BI applications that address financial management, compliance, and profitability and cost management.

Program Management

Program management includes a strong focus on effective leadership for integrating people, processes, and technology to deliver business value. It requires knowledge of development methodology and program and project management, as well as organizational and team-building skills.
Program management includes project planning and scoping; staffing and structuring the BI team; developing a road map; training and support; vendor negotiations; and sponsoring BI competency centers to ensure governance and IT/business alignment. Related disciplines include business performance management (BPM), customer relationship management (CRM), and supply chain management (SCM).

Master Data Management

Master data management (MDM) is the practice of acquiring, improving, and sharing master data. MDM involves creating consistent defini­tions of business entities via integration techniques across multiple internal IT systems and often to partners or customers. MDM is enabled by integration tools and techniques for ETL, EAI, EII, and replication. MDM is related to data governance, which aims to improve data’s quality, share it broadly, leverage it for competitive advantage, manage change, and comply with regulations and standards.

Source : http://tdwi.org

Friday, August 2, 2013

Indian Companies that are hiring Data Analysts


  1. Google
  2. Amazon
  3. IBM
  4. Citibank
  5. Fidelity
  6. Rediff
  7. Accenture
  8. HSBC
  9. Infosys
  10. Genpact
  11. Mu Sigma
  12. HP
  13. Dell
  14. TATA
  15. IMRB
  16. HCL
  17. iGate
  18. Cognizant
  19. Wipro
  20. Bloomberg
  21. Headstrong
  22. McKinsey
  23. Cloudera
These are the initial list. Would keep on adding.