Sisense
JULY 24, 2019
Last, and still a very painful challenge for most users, is the familiarity with the underlying data and data model. NLQ is gaining traction in the big data analytics tools domain for its quick answers and ease of use. In other words, how the variables are named, and the granularity of their values.
Sisense
MAY 27, 2019
Often with a background in advanced mathematics and/or statistical analysis, data scientists conduct high-level market and business research to help identify trends and opportunities, and then, to summarize, these findings are presented by the business analyst to the business and stakeholders in a manner that aids decision-making.
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Data Pine
MARCH 31, 2022
Many solutions require the use of different programming languages to perform advanced analysis such as R, Python, Javascript, just to name a few, and knowing them can significantly enhance your skillset. This could involve anything from learning SQL to buying some textbooks on data warehouses.
Sisense
JANUARY 15, 2021
This is one of the reasons we’ve seen the rise of data teams — they’ve grown beyond Silicon Valley startups and are finding homes in Fortune 500 companies. As data has become more massive, the technical skills needed to wrangle it have also increased. Situation #2: Established company creates a data team for deeper insights.
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