Compression algorithm in data example

Compression algorithm in data example. 3 Framework For the remainder of this lecture, we consider the following problem: Jul 8, 2024 · Lossless compression is a class of data compression algorithms that allows the original data to be perfectly reconstructed from the compressed data. Compression. As a result of compression, administrators spend less money and less time on storage. JPEG, MPEG) are lossy—decompressing the compressed result doesn't recreate a perfect copy of the original. By operation of the pigeonhole principle, no lossless compression algorithm can shrink the size of all possible data: Some data will get longer by at least one symbol or bit. Typically, it has a smaller (i. This section under major construction. Over the past several decades, computer scientists have been developing and perfecting different algorithms for data compression. g. But first, let’s go over some basic terms. Sep 19, 2019 · developing a scalable compression algorithm that exploits this model’s theoretical compression potential. When this procedure is applied to the string in question, the first character. The PNG specification defines a single compression method, the deflate algorithm, for all image Jul 12, 2022 · One way to efficiently apply these data compression algorithms is by using them as part of a dedicated deep learning (DL) neural network. It means that lossless compression algorithms can accurately reconstruct the original data from the compressed data. Data compression is a crucial process in computing, responsible for reducing the size of data files or streams while preserving most of the original information. Example of lossless data compression technique is text compression. Deflate, zlib, gzip — three names intertwined. If you're seeing this message, it means we're having trouble loading external resources on our website. ALTER TABLE ColumnstoreTable1 REBUILD PARTITION = ALL WITH ( DATA_COMPRESSION = COLUMNSTORE ON PARTITIONS (4, 5), DATA COMPRESSION = COLUMNSTORE_ARCHIVE ON PARTITIONS (1, 2, 3) ); Performance The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. This results in a prefix-free binary code meaning no code is a prefix of the another. PNG images use lossless compression while JPEG images can and often do use lossy compression. 1. LZW compression; RLE compression; Lossy algorithms achieve better compression ratios by selectively getting rid of some of the information in the file. On the previous example, this would give the following: WW12BWW12BB3WW24BWW14. Data Compression Algorithms works by identifying and eliminating redundant or unnecessary information from the data. Apr 9, 2024 · It can be done in two ways- lossless compression and lossy compression. Sep 11, 2023 · Huffman coding is a popular algorithm used for the lossless data compression. Our approaches are mainly algorithmic. It is an application of lossless data compression. Compression Process Example. is “i” and the string consisting of just that character is already in the dictionary. Compression algorithms can be either adaptive or non-adaptive. Lempel–Ziv–Welch (LZW) is a universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. Compression can be either lossless or lossy. Compression algorithms are usually effective for human- and machine-readable documents and cannot shrink the size of random data that contain no redundancy. Resources. It is used to This concept allows arithmetic coding to adapt to the content as it’s encoding which allows it to achieve a higher compression ratio. Named after Algorithm Example Shortcomings Variations: The Concept. Sep 20, 2023 · Data Types Data-type in simple terms gives us information about the type of data. This can save storage space and reduce transmission time when sending files over the internet. PNG - which stands for Portable Network Graphic - is a lossless image file type that allows you to restore the original file after compression. It’s beneficial when storage and bandwidth efficiency trump the need for perfect image fidelity. The compression ratio of the resulting compression scheme heavily relies on the first problem: the model capacity. Here is an example of the algorithm being run on an ideal input. 6. Compression quality can be measured in various ways. If you're behind a web filter, please make sure that the domains *. sort then in ascending order of their frequencies. On the other hand, a lossless compression algorithm is a compression algorithm that doesn’t remove any information when compressing a file, and all information is restored after 3 days ago · An example is a simple dictionary built into the compression algorithm scheme. Aug 7, 2024 · Union By Rank and Path Compression in Union-Find Algorithm; Introduction to Disjoint Set Data Structure or Union-Find Algorithm; Shortest Path in Graph: Dijkstra’s shortest path algorithm; Bellman–Ford Algorithm; Floyd Warshall Algorithm; Johnson’s algorithm for All-pairs shortest paths; Shortest Path in Directed Acyclic Graph; Dial’s . 2 Lempel–Ziv–Welch. kasandbox. Figure 3. The opposite would be a lossy compression algorithm. Some of the compression algorithms (e. Moore's law: # transistor on a chip doubles every 18-24 months. Example, integer, character, etc. The Huffman code is an example of a code which is optimal in the case where all symbols probabilities are integral powers of 1/2. As compare to lossless data compression, lossy data compression holds less data. The following is a (non-exhaustive) list of topics of interests: Loss-less data compression; Lossy data compression; Algorithms on compressed data; Compressed data Overview of Data Compression and Its Benefits. The following algorithms are lossy: JPEG compression; Which algorithm is best? The other forms of lossless data compression schemes include Lempel–Ziv–Welch Coding (LZW), which find applications in non-signal type data applications as well. Feb 1, 2021 · Near-Lossless compression techniques is an another type of compression technique where the difference between the original and reconstructed data is guaranteed to vary from the respectively values in the original data by no more than a user-specified amount called as maximum absolute distortion (MAD) (Ansari et al. A data structure that stores non overlapping or disjoint subset of elements is called disjoint set data structure. This algorithm makes sure that the most common characters are represented by shorter Data Compression Some of these lecture slides have been adapted from: • Algorithms in C, Robert Sedgewick. . A simple framework that delivers strong loss lessness Data compression that contains several runs of the same value is Run Length Encoding. Lossless compression is generally used for so-called "discrete" data, such as database records, spreadsheets, word-processing files, and even some kinds of image and video information. Lempel-Ziv-Storer-Szymanski. Such algorithms can be used for images or sound files but not for text or program data. Aug 25, 2023 · There are 2 categories of data compression algorithms: lossy and lossless. Algorithms used in Lossy compression are: Transform coding, Discrete Cosine Transform, Discrete Wavelet Transform, fractal compression etc. Lossless vs. One of the fastest compression and decompression algorithms. Aug 16, 2023 · In this article, we will learn the implementation of Huffman Coding in C. 19. e. In the face of the shortage of radio spectrum resources, the contradiction between supply and demand and other issues, data compression technology can ensure data integrity while saving storage space, effectively improving the utilization of spectrum resources. , worse) compression ratio than the similar LZO algorithm, which in turn is worse than algorithms like DEFLATE. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points. scale image for our example and following Jul 16, 2024 · Lossy compression reduces the size of data. WHAT IS SHANNON FANO CODING? Shannon Fano Algorithm is an entropy encoding technique for lossless data compression of multimedia. , if there is 11 a s and 5 b s, you just encode them as 11a5b . 7. To save SPACE when storing it. Data compression: reduces the size of a file to save space when storing it and to save time when transmitting it. LZ4 is lossless compression algorithm, providing compression speed > 500 MB/s per core, scalable with multi-cores CPU. Is PNG lossless? Yes. Such an algorithm compresses by "summarizing" the data. , 1998). Lossy data compression methods sacrifice some data to achieve higher compression ratios. Mar 14, 2024 · What are these magical time-series compression algorithms? First of all, they’re not magic, but clever computer science techniques. For example, an audio compression algorithm might reduce the amount of data used for a high-pitched cymbal crash in a song. Lempel-Ziv 77 (LZ77) algorithm is the first Lempel-Ziv compression algorithm for sequential data compression. The compression technology is briefly introduced any file back in to the original file [5, 8, 9]. However, LZ4 compression speed is similar to LZO and several times faster than DEFLATE, while decompression speed Sep 14, 2022 · Run–length encoding (RLE) is a simple form of lossless data compression that runs on sequences with the same value occurring many consecutive times. Data compression is like packing your suitcase; it's all about fitting a large amount of data into a smaller space. Lossy compression reduces the size of data by removing unnecessary information, while there is no data loss in lossless compression. Data-types are classified as: Primitive or Built-in data types Some of the examples of primitive data types are as follows Variable named ch refers to the memory address 100 In computing, Deflate (stylized as DEFLATE, and also called Flate [1] [2]) is a lossless data compression file format that uses a combination of LZ77 and Huffman coding. It uses the same token concept with an offset and length to tell the decoder where to copy the text, except it only places the token when the token is shorter than the text it is replacing. the popular file format like ZIP file format that is used for compression of data files. Given some data points, we can compute the optimal codebook and the corresponding partition of the data points. When needed, the data can be uncompressed, or decoded and retrieved. Each letter of the alphabet is coded as a sequence of dots and dashes. Sep 3, 2021 · Lossless Compression Algorithms# As the name implies the lossless compression algorithms belong to a category of data compression algorithms that compress the files without losing any of their content. File quality is low in the lossy data compression. Recent advances in deep learning allow us to optimize probabilistic models of complex high-dimensional data efficiently. Lossy Compression. Huffman in 1952 a Why is data compression important? Data compression can dramatically decrease the amount of storage a file takes up. a priori expectations and usually rely on studying the particular data file contents to find redundancy and patterns that allow for compression. Mar 24, 2023 · Time complexity: O(ElogV) where E is the number of edges in the graph and V is the number of vertices. org are unblocked. Alphabets following a geometric distribution will have a Golomb code as an optimal prefix code, [1] making Golomb coding highly suitable for situations in which the occurrence of small values in the input stream is significantly more likely than large values. The following figure illustrates sequential tasks of the data compression algorithm. The series begins with the Lempel-Ziv Lossless Data Compression Algorithm, commonly known as LZ77. this book is nicely written and well organized. Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. … the author has done a very good job in explaining all these complicated concepts, and presenting related algorithms and their analysis, with a minimal Aug 14, 2018 · So, for example, if you have a relatively still shot that takes up several seconds in a video, a lot of space gets saved because the compression algorithm doesn't need to store all the stuff in the scene that doesn't change. The process involves two algorithms—one for compression and one for reconstruction. JPEG Compression Algorithm. Data compression is an interesting and active research area. LZAV is a fast general-purpose in-memory data compression algorithm based on now-classic LZ77 lossless data compression method. Apr 15, 2013 · Data compression is the art of reducing the number of bits needed to store or transmit data. This is achieved through neuron pruning and shuffling, the former conducted through merging an arbitrary number of weight values according to a constructed distance matrix May 4, 2017 · Lossless compression is it does not loose data when compression happens and it can be regenerated to the original image. Deflate is the algorithm used by the zlib and gzip implementations. Aug 26, 2016 · 5. Losslessly compressed data can be decompressed to exactly its original value. This can determine if two elements are in Introduction Algorithm - DCT - Coefficient Quantization - Lossless Compression Color Future. This Lossless data compression can be grouped into two categories [15],[16]: Fig. This would be interpreted as a run of twelve Ws, a B, a run of twelve Ws, a run of three Bs, etc. Interframe compression is the main reason we have digital TV and web video at all. It efficiently reduces the amount of data required to represent information, leading to optimized storage and faster data transmission. To name a few, Burrows–Wheeler transform is used in algorithms for sequence alignment, image compression, data compression, etc. Golomb in the 1960s. Jan 16, 2024 · Remember, lossy image compression data is irreversible, and over-compression can lead to noticeable quality loss. Data compression is commonly used in various domains, including computer science, telecommunications, and data storage. Limited Applicability: LZW compression is particularly effective for text-based data, but may not be as effective for other types of data, such as images or video, which have Ida Mengyi Pu, in Fundamental Data Compression, 2006. Later in this article, we’ll take a look at two practical examples of image compression using deep learning models. 4. The following table shows the input stream that is used for this compression example. If no match is found, the algorithm outputs a null-pointer and the byte at the coding position. File quality is high in the lossless data compression. 5. The Discrete Cosine Transform (DCT) The key to the JPEG baseline compression process is a mathematical transformation known as the Discrete Cosine Transform (DCT). Dec 14, 2022 · What is a Disjoint set data structure?Two sets are called disjoint sets if they don't have any element in common, the intersection of sets is a null set. Dictionary Data Compression -Lecture 19 3 LZW Encoding Algorithm Repeat find the longest match w in the dictionary output the index of w put wa in the dictionary where a was the unmatched symbol Dictionary Data Compression -Lecture 19 4 LZW Encoding Example (1) Dictionary 0 a 1 b a b a b a b a b a Dictionary Data Compression -Lecture 19 5 May 10, 2024 · Huffman coding is a popular algorithm used for the lossless data compression. 5: LZW encoding algorithm. • Non-adaptive – assumes prior knowledge of the data (e. 2 Data Compression Compression reduces the size of a file: To save TIME when transmitting it. Coding redundancy refers to the redundant data caused due to suboptimal coding techniques. An example is 1848 Morse Code. If you’re interested in learning more about arithmetic coding, check out these great resources: Mark Nelson - Data Compression With Arithmetic Coding; Arithmetic Compression from Compressor Head Oct 29, 2011 · Data compression is the art of reducing the number of bits needed to store or transmit data. Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. This is because we are using an array of subsets to store the representative elements of each vertex, and the size of this array is proportional to the number of vertices. It reports times and compression ratios for 100s of compression algorithms over many databases. Sep 12, 2019 · In this post we are going to explore LZ77, a lossless data-compression algorithm created by Lempel and Ziv in 1977. A Huffman code can be built in the following manner: Data compression is an interesting and active research area. It was published by Welch in 1984 as an improved implementation of the LZ78 algorithm published by Lempel and Ziv in 1978. • Adaptive – assumes no knowledge of the data, but builds such knowledge. Sep 19, 2023 · At a high level, data compression works by encoding the original, target data in fewer bits, reducing the size of the data. Oct 17, 2023 · Basic Technique for Data Compression. Aug 27, 2024 · Data compression, the process of reducing the amount of data needed for the storage or transmission of a given piece of information, typically by the use of encoding techniques. How Data Compression Algorithms Works. If you already know the most compact storage scheme for a specific type of data, then you can simply substitute the more compact state for the actual data. Apr 19, 2024 · A disjoint-set data structure is defined as one that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. Aug 10, 2017 · Lempel–Ziv–Oberhumer (LZO) is one of the well-known data compression algorithms that is lossless and focused on decompression speed. Hence, we can divide the data compression algorithms into two broad categories: lossless and lossy data compression. Lossless compression methods are reversible. It assigns variable-length codes to input characters, with shorter codes assigned to more frequent characters. LZW is another popular form of lossless data compression. Jul 2, 2018 · The algorithm for creating a Huffman tree is explained and then how it is Talking about how Huffman coding can be used to compress data in a lossless manner. This article first makes lossless Huffman coding, LZ77, LZ78, and LZW algorithms. For example, in a 2:1 compression ratio, a 20 megabyte file takes up 10 MB of space. The main idea is to do each-step iteratively: Given a codebook, compute the best partition of the data points; Given a partition of the data points, compute the optimal codebook; Repeat until convergence The lossless quality of Burrows algorithm has provided for different algorithms with different purposes in mind. Consider the following text and its symbol frequencies: Consider the PTSP, the compression algorithm used in [90], is a prime example of lossless compression, visible in the complete recovery of the weight tensors communicated in the network. The compression is lossless, i. Because the words are swapped out for their matching codes, the input file is compressed. Parkinson's law: data expands to fill available space. A union-find algorithm is an algorithm that performs two useful operations on such a data structure: Find: Determine which subset a particular element is in. Jul 1, 2024 · Last update: July 1, 2024 Translated From: e-maxx. The compression algorithm gives you highly detailed graphics without losing any essential data, making them a great file type for prominent photos, company logos and other valuable web images. But Lossless Compression does not reduce the size of data. What is Huffman Coding?Huffman Coding is a lossless data compression algorithm. The dictionary is a portion of the previously encoded sequence. ru Disjoint Set Union¶. The goal of video and audio compression is to maximize the compression ratio and to minimize the distortion; a common trade-off in all compression technologies. Often it is also called Union Find because of its two main operations. If data have been losslessly compressed, the original data can be recovered exactly from the compressed data after a compress/expand cycle. The question that we want to answer is how and how much the replacement of a sub– optimal strategy by an optimal one influences the performance of a data compression algorithm. Different If you're seeing this message, it means we're having trouble loading external resources on our website. 2. Lempel-Ziv-Storer-Szymanski, which we’ll refer to as LZSS, is a simple variation of the common LZ77 algorithm. , "LZP: a new data compression algorithm Feb 21, 2006 · This is the first lesson in a new series of lessons that will teach you about data and image compression. 1 The Lempel-Ziv algorithm There is a sense in which the Huffman coding was “optimal”, but this is under several assumptions: 1. Jul 27, 2021 · Compression reduces the cost of storage, increases the speed of algorithms, and reduces the transmission cost. LZ77 iterates sequentially through the input string and stores any new match into a search buffer. Mar 18, 2024 · However, there were some issues with the compression algorithms. Future lessons will cover a variety of compression schemes, including: Huffman data encoding; Run-length data encoding; GIF image compression As compare to lossy data compression, lossless data compression holds more data. These techniques are used to reduce data size for storing, handling, and transmitting content. This type of compression is commonly used in multimedia formats like JPEG for images and MP3 for audio. Arithmetic Coding for Data Compression Paul Howard and Jeffrey Vitter describe an efficient implementation which uses table lookups in the article from 1994. Mar 10, 2020 · Lossy compression algorithms deliver compression ratios that are high and represent most multimedia compression algorithms in image, video, and audio content. This algorithm is simple in implementation and highly used for compressing GIF, TIFF, and PDF files. When lossy compression is permitted, as for video, other algorithms can K-means Algorithm. In some ways compression is responsible for the very existence of the Portable Network Graphics format (recall Chapter 1, "An Introduction to PNG"), and it is undoubtedly one of the most important components of PNG. The following very short text 'abc' has been compressed using the deflate algorithm outputting 'eJxLTEoGAAJNASc=' which in binary notation is: For the benefit of those who appreciate seeing algorithms written like a computer program, this encoding algorithm is shown in Figure 3. The following is a compilation of some uses given to the Burrows–Wheeler Transform. Here are the set of compression algorithms we'll explain, grouped by data type: Integer compression: Delta encoding; Delta-of-delta encoding; Simple-8b; Run-length encoding; Floating point compression: XOR-based May 6, 2023 · Common Data Compression Algorithms and Their Uses. to systematically compare lossless compression algorithms is the Archive Comparison Test (ACT) by Jeff Gilchrist. The encoder examines the input sequence through a sliding window as shown in Figure 9. Compression is achieved by removing redundancy, that is repetition of unnecessary data. kastatic. This makes it a great option for compressing sensitive data or important files. Note that & is an End of File character: ↑ Bloom, C. May 24, 2011 · My opinion will be, first decide whether you want to do a lossless compression or a lossy compression, then pick an algorithm to implement. Aug 31, 2016 · While lossless data compression is the focus of this post, there exists a related but very different field of lossy data compression, used primarily for images, audio, and video. It encodes the sequence to store only a single value and its count. There are many good reasons to study compression algorithms. While lossy data compression results in a substantial reduction in file size, there’s also some loss of quality. The thesis of Paul Howard from 1993 about data compression algorithms with emphasis on arithmetic coding, text and image compression. This algorithm is widely spread in our current systems since, for instance, ZIP and GZIP are based on LZ77. 5 Data Compression. Apr 10, 2023 · The compression algorithm solves this problem by outputting after the pointer the first byte in the lookahead buffer after the match. for all the unique characters: create a newNode extract minimum value from Q and assign it to leftChild of newNode extract minimum value from Q and assign it to rightChild of newNode calculate the sum of these two minimum values and assign it to the value The Importance of Data Compression. Summary. Let’s learn about a few of them: The Deflate Compression Algorithm. Some of the most Huffman Coding Algorithm create a priority queue Q consisting of each unique character. It was designed by Phil Katz, for version 2 of his PKZIP archiving tool. "The current book is intended for people interested in a basic understanding of the increasingly important field of data compression … . A few compression algorithms can perform lossy compression. In this tutorial, we’ll discuss a lossless algorithm called arithmetic encoding (AE). There are two types of compression: Lossless: Preserves In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. Compression algorithms can be classified as two broad classes: lossless and lossy compressions. Sep 24, 2022 · Huffman coding (also known as Huffman Encoding) is an algorithm for doing data compression, and it forms the basic idea behind file compression. Oct 27, 2023 · This next example sets the data compression to columnstore on some partitions, and to columnstore archival on other partitions. It works by assigning variable-length codes to input characters with the shorter codes assigned to more frequent characters. Space complexity: O(V), where V is the number of vertices. We analyze three algorithms, each in a different domain of data compression: Sep 4, 2023 · Example 1: Huffman Coding for Text Compression Let’s illustrate the Huffman coding algorithm with a text compression example. IPP LZO is one of the numerous LZO methods with the medium compression ratio, and it shows very high decompression performance Jan 2, 2022 · Conclusion: Rice coding is a powerful technique in data compression, especially suitable for integer data with repetitive patterns. Lossless compression is a special type of compression of information the algorithm requires the reduction of bits by recognising and removing Redundancy in statistics. Today, many different algorithms are in use, with some being more effective for video and others for images. May 28, 2020 · In this article, you will discover six different types of lossless data compression algorithms, and four image and video compression algorithms based on deep learning. The algorithm was developed by the David A. Nov 30, 2019 · We invite you to submit high quality papers to this Special Issue on “Data compression and applications”, with subjects covering the whole range from theory to applications. Here are a few pointers: Here are a few pointers: For the lossless one, some are very intuitive, such as the run-length encoding, e. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data The LZ4 algorithm aims to provide a good trade-off between speed and compression ratio. Golomb coding is a lossless data compression method using a family of data compression codes invented by Solomon W. org and *. , character frequncies). Mar 18, 2024 · A lossy compression algorithm is a compression algorithm that permanently removes some data from the original file, especially redundant data, when compressing it. It also gives a score based on a weighted average of runtime and the compression ratio. Design Example: Data Compression Algorithm In this section, an example design of the data compression algorithm is presented to show how it influences the total system performance. Most humans cannot hear sounds above 18kHz, so any frequency details above this threshold can be safely stripped from the audio data. Lossy compression can remove data from a file. One of the key features of BWT is its ability to group together similar characters in a string, which is a key factor in achieving efficient compression. One other matter is the application of additional compression algorithms. It features an extremely fast decoder, with speed in multiple GB/s per core, typically reaching RAM speed limits on multi-core systems. LZAV holds a good position on the Pareto landscape of factors, among many similar in-memory (non-streaming) compression algorithms. It has been under development since either 1996 or 1998 by Igor Pavlov [ 1 ] and was first used in the 7z format of the 7-Zip archiver. Lossy Compression Algorithms. This article discusses the data structure Disjoint Set Union or DSU. uncompressing the compressed file yields exactly the original file. This post talks about the fixed-length and variable-length encoding, uniquely decodable codes, prefix rules, and Huffman Tree construction. When a user sends the compressed data over the internet, the file received may or may not contains the same data as the original file. • Introduction to Data Compression, Guy Blelloch. Jan 31, 2023 · LZW Compression When the input data is processed, the compression algorithm keeps a dictionary corresponding to the longest words encountered with a list of code values. LZO Example in IPP. Examples of lossless compression include gzip, brotli, Zstandard, WebP, and PNG. Huffman in 1952 a Jul 23, 2021 · I am really interested to see a numerical example how deflate compression works, by hand. In data where runs are less frequent, this can significantly improve the compression rate. Compression predates digital technology, having been used in Morse Code, which assigned the shortest codes to the most May 21, 2024 · Compression Speed: LZW compression can be slower than some other compression algorithms, particularly for large files, due to the need to constantly update the dictionary. Data-types in C language are declarations for the variables. Algorithms used in Lossless compression are: Run Length Encoding, Lempel-Ziv-Welch, Huffman Coding *Huffman compression* is a statistical data compression technique which gives a reduction in the average code length used to represent the symbols of a alphabet. You’ll see how AE works through an example that shows the steps of encoding and decoding a message. The disjoint set data structure supports following operations: Adding new sets to A lossless compression algorithm compresses data such that it can be decompressed to achieve exactly what was given before compression. of the effects of using an optimization procedure in a data compression algorithm. For example, consider a screen containing plain black text on a solid white background. There are two main types of data compression algorithms: lossless Mar 18, 2024 · It’s a powerful data transformation method that is used in a lossless data compression algorithm. Data compression can be used in an array of scenarios, reducing image, video, or text files—and is particularly helpful when you’re dealing with large amounts of data that has an underlying pattern (even if you can’t see the pattern yourself!). gkx qiso xuo dvuqfyrd yxeu kmmyku fxrkoug ypqevbd ujfnv vobug