[incubator-datasketches-website] branch master updated: Minor edits.

[le...@apache.org]

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leerho pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-datasketches-website.git


The following commit(s) were added to refs/heads/master by this push:
     new 602ef75  Minor edits.
602ef75 is described below

commit 602ef75b0f8dbbf0f5d719280a4901ba1a4c3f5d
Author: Lee Rhodes <le...@users.noreply.github.com>
AuthorDate: Tue May 26 22:16:10 2020 -0700

    Minor edits.
---
 docs/Community/KDD_Tutorial_Summary.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/Community/KDD_Tutorial_Summary.md b/docs/Community/KDD_Tutorial_Summary.md
index 049fdf3..b94bdfa 100644
--- a/docs/Community/KDD_Tutorial_Summary.md
+++ b/docs/Community/KDD_Tutorial_Summary.md
@@ -26,7 +26,7 @@ layout: blank_page
 
 Speed, cost, and scale. These are 3 of the biggest challenges in analyzing big data. While modern data systems continue to push the boundaries of scale, the problems of speed and cost are fundamentally tied to the size of data being scanned or processed. Processing thousands of queries that each access terabytes of data with sub-second latency remains infeasible. Data sketching techniques provide means to drastically reduce this size, allowing for real-time or interactive data analysis w [...]
 
-This tutorial covers a number of useful data sketching and sampling methods and demonstrate their use using the Apache DataSketches project. We focus particularly on common analytic problems such as counting distinct items, quantiles, histograms, heavy hitters, and aggregations with large group-bys. For these, we covers algorithms, techniques, and theory that can aid both practitioners and theorists in constructing sketches and designing systems that achieve desired error guarantees. For [...]
+This tutorial covers a number of useful data sketching and sampling methods and demonstrate their use using the Apache DataSketches project[3]. We focus particularly on common analytic problems such as counting distinct items, quantiles, histograms, heavy hitters, and aggregations with large group-bys. For these, we covers algorithms, techniques, and theory that can aid both practitioners and theorists in constructing sketches and designing systems that achieve desired error guarantees.  [...]
 
 ## Audience
 


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